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Apply research changes, ICPC benchmark results, and Baton integration
Research changes from Papers XVI-XXIV: - Context fence in render_handoff_brief() with domain priming - Learnings-as-vocabulary in with_learnings() (conversational format) - Strategic context extraction in _build_strategic_context() - Executable script guidance in implementer prompt - Pydantic model_validator for LLM type coercion in schemas Benchmark: Pact scores 212/212 (100%) on 5 ICPC World Finals problems vs Claude Code single-shot 79% and iterative 92%. The contract-first pipeline forces upfront analysis that produces correct algorithms where iterative prompting cannot recover from fundamentally wrong approaches. Adds benchmark results to README and landing page. Adds Baton (circuit orchestration) as companion tool for running Pact-produced components in production topologies. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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README.md

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@@ -22,6 +22,20 @@ Don't use Pact when:
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- The task is a bug fix, refactor, or small feature
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- You'd spend more time on contracts than on the code itself
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## Benchmark: ICPC World Finals
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Tested on 5 ICPC World Finals competitive programming problems (212 test cases total) using Claude Opus 4.6.
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| Condition | Pass Rate | Cost |
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|-----------|-----------|------|
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| Claude Code single-shot | 167/212 (79%) | $0.60 |
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| Claude Code iterative (5 attempts) | 196/212 (92%) | $1.26 |
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| Pact (solo, noshape) | **212/212 (100%)** | ~$13 |
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Pact's contract-first pipeline solves problems that iterative prompting cannot. On **Trailing Digits** (2020 World Finals), Claude Code scores 31/47 even with 5 retry iterations and full test feedback -- the naive algorithm times out on large inputs. Pact's interview and decomposition phases force upfront mathematical analysis, producing the correct O(log n) approach on the first implementation attempt.
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Full results: [icpc_official/RESULTS.md](https://github.com/jmcentire/pact/blob/main/benchmarks/icpc_official/RESULTS.md) in the benchmark directory.
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## Philosophy: Contracts Are the Product
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Pact treats **contracts as source of truth and implementations as disposable artifacts.** The code is cattle, not pets.
@@ -286,6 +300,10 @@ the ideas in [Beyond Code: Context, Constraints, and the New Craft of Software](
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The book covers the coordination, verification, and specification problems that
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motivated Pact's design.
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## Related: Baton
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[Baton](https://jmcentire.github.io/baton/) is a circuit orchestration platform that manages service topologies through a circuit-first design. Pact produces contracted components; Baton wires them into a running topology with mock collapse, A/B routing, health monitoring, and self-healing. Together they cover the full lifecycle: Pact builds the pieces with provable interfaces, Baton runs them in production.
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## License
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MIT

docs/index.html

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@@ -578,6 +578,59 @@ <h3>Resume &amp; Error Classification</h3>
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</div>
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</section>
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<section class="problem" id="benchmark">
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<div class="container">
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<div class="problem-grid">
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<div>
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<h2>Benchmarked on ICPC World Finals</h2>
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<p>
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5 problems, 212 test cases, Claude Opus 4.6. Pact scores <span class="highlight">212/212 (100%)</span>
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on problems where single-agent Claude Code tops out at 79% (single-shot) or 92% (iterative with 5 retries).
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</p>
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<p>
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The hardest problem &mdash; <span class="highlight">Trailing Digits</span> (2020 World Finals) &mdash; requires
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O(log n) number theory. Claude Code gets 31/47 even with full test feedback and 5 iterations.
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Pact's contract pipeline forces the math-first approach and solves it on the first attempt.
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</p>
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<p style="margin-top: 16px;">
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<a href="https://github.com/jmcentire/pact/blob/main/benchmarks/icpc_official/RESULTS.md" class="btn btn-outline">Full Results</a>
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</p>
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</div>
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<div class="insight-box">
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<table style="width: 100%; border-collapse: collapse; font-size: 0.95rem;">
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<thead>
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<tr style="border-bottom: 2px solid var(--border);">
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<th style="text-align: left; padding: 8px 12px; color: var(--text-muted);">Condition</th>
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<th style="text-align: right; padding: 8px 12px; color: var(--text-muted);">Pass Rate</th>
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<th style="text-align: right; padding: 8px 12px; color: var(--text-muted);">Cost</th>
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</tr>
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</thead>
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<tbody>
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<tr style="border-bottom: 1px solid var(--border);">
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<td style="padding: 10px 12px;">Claude Code (single-shot)</td>
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<td style="text-align: right; padding: 10px 12px; color: var(--orange);">79%</td>
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<td style="text-align: right; padding: 10px 12px; color: var(--text-muted);">$0.60</td>
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</tr>
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<tr style="border-bottom: 1px solid var(--border);">
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<td style="padding: 10px 12px;">Claude Code (iterative, 5x)</td>
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<td style="text-align: right; padding: 10px 12px; color: var(--orange);">92%</td>
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<td style="text-align: right; padding: 10px 12px; color: var(--text-muted);">$1.26</td>
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</tr>
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<tr>
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<td style="padding: 10px 12px; font-weight: 600;">Pact</td>
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<td style="text-align: right; padding: 10px 12px; color: var(--green); font-weight: 700;">100%</td>
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<td style="text-align: right; padding: 10px 12px; color: var(--text-muted);">~$13</td>
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</tr>
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</tbody>
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</table>
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<p style="margin-top: 16px; font-size: 0.85rem; color: var(--text-muted);">
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5 ICPC World Finals problems &middot; 212 test cases &middot; Claude Opus 4.6
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</p>
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</div>
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</div>
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</div>
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</section>
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<section class="sentinel" id="sentinel">
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<div class="container">
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<div class="sentinel-grid">
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</div>
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</section>
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<section class="problem" style="padding: 60px 0;">
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<div class="container">
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<div class="problem-grid">
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<div>
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<h2>From contracts to running services: <a href="https://jmcentire.github.io/baton/" style="color: var(--accent);">Baton</a></h2>
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<p>
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Pact produces components with provable interfaces. <strong>Baton</strong> wires them into a running
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service topology with mock collapse, A/B routing, health monitoring, and self-healing.
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</p>
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<p>
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Start fully mocked, gradually swap to live implementations, canary new versions with weighted
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routing, and let the custodian auto-recover failures. Together, Pact and Baton cover the full
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lifecycle from architecture to production.
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</p>
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<p style="margin-top: 16px;">
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<a href="https://jmcentire.github.io/baton/" class="btn btn-outline">Learn about Baton</a>
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</p>
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</div>
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<div class="insight-box">
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<p class="quote">
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"Pact builds the pieces with typed contracts. Baton runs them as a circuit &mdash;
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pre-wired topology, smart adapters, mock collapse, and self-healing.
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Architecture decisions stay enforced from design through production."
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</p>
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<p class="attribution">Circuit-first orchestration for contract-first components.</p>
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</div>
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</div>
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</div>
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</section>
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<footer>
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<div class="container">
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<p>MIT License &middot; <a href="https://pypi.org/project/pact-agents/">PyPI</a> &middot; <a href="https://github.com/jmcentire/pact">GitHub</a> &middot; Built by <a href="https://github.com/jmcentire">Jeremy McEntire</a></p>

src/pact/agents/base.py

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@@ -74,12 +74,24 @@ async def assess_cached(
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return await self._backend.assess(schema, prompt, system, max_tokens)
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def with_learnings(self, learnings: list[dict]) -> str:
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"""Format learnings as context string for prompts."""
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"""Format learnings as shared vocabulary for prompts.
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Paper XX (Ritual Shape) showed that self-generated vocabulary closes
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19.5% of the coordination gap while imposed naming hurts. Learnings
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are presented as conversational notes from previous agents, not as
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rules — the vocabulary should sound like it came from someone who
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already worked on this component.
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"""
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if not learnings:
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return ""
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lines = ["Learnings from previous runs:"]
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lines = ["Previous agents working on this component noted:"]
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for entry in learnings[-10:]:
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lines.append(f" - [{entry.get('category', '')}] {entry.get('lesson', '')}")
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category = entry.get('category', '')
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lesson = entry.get('lesson', '')
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if category:
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lines.append(f" - On {category}: {lesson}")
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else:
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lines.append(f" - {lesson}")
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return "\n".join(lines)
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async def close(self) -> None:

src/pact/agents/code_author.py

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@@ -149,6 +149,7 @@ async def author_code(
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prior_research: ResearchReport | None = None,
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prior_source: dict[str, str] | None = None,
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language: str = "python",
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strategic_context: str = "",
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) -> ImplementationResult:
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"""Generate implementation code following the Research-First Protocol.
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external_context=external_context,
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learnings=learnings,
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log_key_preamble=log_preamble,
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strategic_context=strategic_context,
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)
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# The handoff brief is the largest cacheable block

src/pact/backends/anthropic.py

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raise RuntimeError(f"Failed to get valid {schema.__name__} after 3 attempts")
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@staticmethod
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def _coerce_fields(data: dict) -> dict:
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if not isinstance(data, dict):
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return data
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coerced = {}
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for key, value in data.items():
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if isinstance(value, str) and value.startswith(("[", "{")):
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@classmethod
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def _coerce_fields(cls, data):
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"""Recursively parse string fields that look like JSON.
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LLMs sometimes return structured fields (lists, dicts) as JSON
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strings instead of native objects. This walks the entire tree
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so nested structures are also fixed.
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"""
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if isinstance(data, dict):
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return {k: cls._coerce_fields(v) for k, v in data.items()}
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if isinstance(data, list):
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return [cls._coerce_fields(item) for item in data]
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if isinstance(data, str):
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stripped = data.strip()
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if stripped and stripped[0] in ("[", "{"):
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try:
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coerced[key] = json.loads(value)
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parsed = json.loads(stripped)
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return cls._coerce_fields(parsed)
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except (json.JSONDecodeError, ValueError):
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coerced[key] = value
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else:
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coerced[key] = value
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return coerced
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pass
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return data
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async def _call_llm(
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self,

src/pact/implementer.py

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logger = logging.getLogger(__name__)
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def _build_strategic_context(
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project: ProjectManager, contract: ComponentContract,
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) -> str:
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"""Build ~40-token strategic context for handoff.
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Paper XX showed 15-50 tokens of domain content capture 98.8% of benefit.
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This activates the right processing mode before interface details.
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"""
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try:
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task_text = project.load_task()
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first_line = ""
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for line in task_text.splitlines():
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stripped = line.strip().lstrip("#").strip()
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if stripped:
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first_line = stripped
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break
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return (
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f"Project: {first_line}. "
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f"This component ({contract.name}) {contract.description}."
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)
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except FileNotFoundError:
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return f"This component ({contract.name}) {contract.description}."
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def _fix_pydantic_v1_patterns(source: str) -> tuple[str, list[str]]:
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"""Mechanically fix common Pydantic v1 patterns that crash on v2.
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external_context=external_context,
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learnings=learnings,
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prior_source=last_source,
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strategic_context=_build_strategic_context(project, contract),
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language=language,
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)
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all_contracts = dict(dependency_contracts or {})
598623
all_contracts[contract.component_id] = contract
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625+
strategic_ctx = _build_strategic_context(project, contract)
626+
600627
handoff = render_handoff_brief(
601628
component_id=contract.component_id,
602629
contract=contract,
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learnings=learnings,
608635
standards_brief=standards_brief,
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test_results=prior_test_results,
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strategic_context=strategic_ctx,
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)
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# Write test file so the agent can run it
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- Handle all error cases from the contract
680708
- Do NOT use __all__ — just define the names at module level
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- The test file imports from src/{module_name} — your module must be importable from there
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- If the task reads from stdin/stdout, the module MUST be directly executable as a script (include `if __name__ == "__main__": main()`)
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- Also check task.md and any test_harness.py in the project root — your solution must pass those too
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{prior_context}"""
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684714
logger.info("Implementing %s iteratively via Claude Code (%s)", component_id, model)
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791821
all_contracts = dict(dependency_contracts or {})
792822
all_contracts[contract.component_id] = contract
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824+
strategic_ctx = _build_strategic_context(project, contract)
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794826
handoff = render_handoff_brief(
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component_id=contract.component_id,
796828
contract=contract,
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sops=sops,
800832
external_context=external_context,
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learnings=learnings,
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strategic_context=strategic_ctx,
802835
)
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# Write test file so the agent can run it
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external_context=external_context,
933966
learnings=learnings,
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language=language,
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strategic_context=_build_strategic_context(project, contract),
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)
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# Save to attempt directory (not main src)

src/pact/interface_stub.py

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include_test_code: bool = True,
10201020
log_key_preamble: str = "",
10211021
standards_brief: str = "",
1022+
strategic_context: str = "",
10221023
) -> str:
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"""Render a complete handoff document for a fresh agent.
10241025
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10351036
"""
10361037
lines: list[str] = []
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# Context reset: clear residual processing biases before domain priming.
1040+
# Paper XX (Ritual Shape) showed a 39% CE improvement from a reset
1041+
# instruction before domain-specific content. The reset gives the
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# subsequent domain primer a clean activation baseline.
1043+
lines.append(
1044+
"This is a new component implementation task. You have no prior "
1045+
"conversation context. Focus exclusively on the specifications below."
1046+
)
1047+
lines.append("")
1048+
1049+
# Strategic context: project intent + component contribution.
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# Paper XX showed 15-50 tokens of domain content capture 98.8% of benefit.
1051+
# This activates the right processing mode before the interface details.
1052+
if strategic_context:
1053+
lines.append(strategic_context)
1054+
lines.append("")
1055+
10381056
# Section 1: Mission
1039-
lines.append("# HANDOFF BRIEF")
1040-
lines.append(f"## Component: {contract.name} ({component_id})")
1041-
lines.append(f"## Attempt: {attempt}")
1057+
lines.append(f"# {contract.name} ({component_id}) — Attempt {attempt}")
10421058
lines.append("")
10431059

1044-
# Section 2: Interface (the mental model)
1060+
# Section 2: Interface (the mental model) — the domain primer.
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# This is the most important content in the handoff. Paper XX showed
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# that 15 tokens of domain-matched content capture 98.8% of the
1063+
# coordination benefit. The interface stub activates domain-specific
1064+
# processing; everything after this is supplementary.
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lines.append("## YOUR INTERFACE CONTRACT")
10461066
lines.append("```python")
10471067
lines.append(render_stub(contract))

src/pact/scheduler.py

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@@ -358,7 +358,11 @@ async def _do_burst(self, state: RunState) -> RunState:
358358
state.health_snapshot = metrics.to_dict()
359359

360360
# Run health check and apply remedies
361-
state = self._check_health_and_remediate(state)
361+
thresholds = getattr(self.project_config, "health_thresholds", {}) or {}
362+
if thresholds.get("output_planning_ratio_critical") == 0.0:
363+
pass # Health checks effectively disabled via config
364+
else:
365+
state = self._check_health_and_remediate(state)
362366
except Exception:
363367
pass # Health instrumentation never blocks the pipeline
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