Make coding agents finish with proof — not vibes.
A portable execution protocol for coding agents. 77 lines. 3 core rules. On-demand profiles.
Download · 3 Rules · Install · 中文 · Benchmarks
--- **No proof, no done.** FP activates automatically for engineering work and stays dormant for casual conversation. Three rules, on-demand profiles, zero ceremony creep. --- ## The Three Rules **1. Diagnose before patching.** Gather evidence. Find root cause. Do not guess. **2. Verify before claiming done.** Run the tests. See them pass. "Implemented" is not "done." **3. Be concise and actionable.** First line = result. Last line = next step or verdict. No filler. For complex work, FP provides on-demand profiles: live systems, multi-agent coordination, provider compatibility, delegated execution, cross-session continuation, and more. They load only when the condition matches — not by default. > **Non-reasoning model?** Use [`fp-minimal/`](fp-minimal/SKILL.md) — just the three rules. No router, no profiles. --- ## Evidence-Based Design (v0.5.0) This version was optimized through **1,416 real LLM API calls** across 3 models, 8 traits, and 3 testing methods. Every design decision is backed by benchmark data. ### Cross-Model Blind Eval | Model | 🥇 Winner | Score | 🥈 | Score | Key Insight | |-------|----------|-------|------|-------|-------------| | gpt-5.3-codex-spark (non-reasoning) | v-minimal | **3.08** | v0 | 3.01 | Weak models need simple instructions | | gpt-5.6-sol (reasoning) | v-final | **3.57** | v0 | 3.49 | Reasoning models leverage structure | | deepseek-v4-pro (reasoning) | v-final | **3.14** | v0 | 2.97 | DeepSeek needs structure even more (v-minimal: 2.46, 7 blockers) | **v-final (77 lines) wins on both reasoning models. v-minimal (3 rules) wins on non-reasoning models. v2 Concise-Max (sacrificing safety for speed) is always worst.** ### E2E Multi-Turn (with real tools) | Metric | Old (162 lines) | New (77 lines) | Improvement | |--------|----------------|---------------|-------------| | Token consumption | 19,620 | 10,665 | **-45%** | | Tool calls | 14 | 6 | -57% | | FP template files read | 9 (3 wasted) | 1 (0 wasted) | **-89%** | | Profile loading | Random | On-demand ✅ | — | ### Templates: 35 → 7 28 templates were never referenced by any on-demand profile. They were dead weight — archive, not delete. The multi-turn test proved agents wasted tokens reading them by default. ### Simulation vs. Reality Our simulation predicted v7 Adaptive-Plus would win at 4.73. Real blind eval showed the opposite — all "optimized" versions performed worse than baseline due to **prompt interference**: adding instructions to an already-balanced system prompt degrades performance. The simulation couldn't model this because it treated each instruction as an independent linear contributor. Full methodology: [`benchmarks/results/ARTICLE.md`](benchmarks/results/ARTICLE.md) --- ## Quick Start ```text Fix the intermittent authentication test. ``` Without FP: increase timeout → run once → "looks fixed." With FP: reproduce → find first divergence → bounded fix → rerun original + regression + negative control → verdict with evidence. ### Install 1. Download [`fp-universal-v0.5.0.zip`](https://github.com/MiaoY0uShan/FP/releases/tag/v0.5.0) 2. Extract and run the installer 3. Reload your agent — FP activates automatically ```powershell .\INSTALL-FP.cmd -Verify # Windows sh ./INSTALL-FP.sh --verify # macOS / Linux ``` Explicit invocations: `FP: fix the bug` or `$fp diagnose the failure` [Full install matrix](INSTALL.md) · [Copy-paste fallback](fp-copy-paste.md) --- ## Protocol | Route | Trigger | Behavior | |-------|---------|----------| | **Small** | One file, ≤5 lines, cause known, no new interface | Tiny Brief + verify | | **Medium** | Multi-file, >5 lines, or added tests | Execution Brief + evidence | | **Vague** | Requirements underspecified | Idea Cards → user picks → Medium | | **Large** | Architectural, multi-module, migration | Decompose → risk-reducing modules | Small is NOT the default. Multi-file = Medium minimum. ### On-Demand Profiles | Condition | Profile | |-----------|---------| | Retry/loop/encoding suspect | `provider-compatibility/SKILL.md` | | Multi-agent, parallel writers | `templates/multi-agent-review-protocol.md` | | Remote/stateful target | `skills/live-system/SKILL.md` | | Unknown failure, diagnosis only | `skills/debug-incident/SKILL.md` | | Cross-session continuation | `skills/continuation/SKILL.md` | | Delegated execution | `delegated-execution/SKILL.md` | | Vague/risky/large requirements | `question-requirements/SKILL.md` | Profiles load **only when the condition matches** — never by default. This was the #1 source of wasted tokens in the old version. --- ## Reuse Ladder Before creating anything: does it need to exist? → already in codebase? → standard library? → native platform? → installed dependency? → one line? → only then add minimum new code. --- ## What You Get | Capability | What it prevents | |---|---| | **Risk-matched routing** | Turning one-line fixes into ceremony — or treating incidents like one-line fixes | | **Debug before patch** | Speculative edits that hide the real cause | | **Reuse before creation** | Unnecessary abstractions, dependencies, files | | **Bounded delegation** | Runaway subagents, overlapping writers | | **On-demand profiles** | Token waste from loading specialized knowledge for simple tasks | | **First-and-last-line gate** | Responses where you can't tell what happened or what's next | --- ## Works Where You Work **Codex · Claude Code · Gemini CLI · Pi · GitHub Copilot · Cursor · Windsurf · Cline · Roo Code · OpenCode · Kiro · Aider · and more** One canonical router. No per-agent methodology. --- ## Run the Benchmarks ```bash # Full blind eval (requires API keys in env) node benchmarks/real-eval-v2.mjs all --versions v0,v-final,v-minimal --trials 2 --model gpt-5.6-sol # Simulation only (no API calls) node benchmarks/score-final.mjs # Multi-turn with real tools node benchmarks/multi-turn-harness-v2.mjs --versions v0,v-final # E2E comparison node benchmarks/e2e-test.mjs ``` Set `FP_API_KEY` and `DEEPSEEK_API_KEY` environment variables before running real evals. --- ## FAQ **Does every task become ceremony?** No. Small tasks get a Tiny Brief. Profiles load on-demand — a simple bug fix loads zero FP templates. **Non-reasoning models?** Use `fp-minimal/SKILL.md`. Three rules. The benchmark data shows this outperforms the full protocol on weaker models. **Why 77 lines?** Because 162 lines caused the agent to waste 45% of its tokens reading FP's own templates. The benchmark data showed exactly which parts added value and which didn't. **Can a subagent declare done?** No. Parent owns integration and reruns critical checks. **Is this autonomous self-modifying AI?** No. Reusable changes require independent evidence, bounded evaluation, and rollback. --- ## Trust Model - Secrets must be redacted from all output. Use `