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The Claude Agent SDK loop (agent/hotpath_agent/loop.py, model claude-fable-5) drives the seven harness tools over a standalone stdio MCP server (mcp_server.py) and runs the full profile -> hypothesize -> patch -> gated-verdict cycle on comrak with no human in the loop. Three audited attempts, all honest rejections, ZERO false accepts: - phase2-comrak-001 class 3: syntect buffer with_capacity, [0.971,1.007] - phase2-comrak-002 class 5: gate dead VecDeque build, [0.982,1.026] - phase2-comrak-003 class 6: hoist find_special_char check, [0.970,1.007] The agent picked the cheapest untried class each time (3->5->6) and TWICE refused to fabricate a verdict it couldn't read back, verifying ledger integrity instead — the anti-reward-hacking behavior SPEC §10 targets. Harness changes surfaced by the loop: - run_verdict is now async: launches the multi-minute build+bench detached (past the 60s MCP transport cap) and returns immediately; new read_verdict op polls the append-only ledger row (ledger verdict_summary). Fixes attempt 001's unreadable-verdict gap. - read_target_source takes offset/limit line windows so 100KB+ files page instead of overflowing — removes the agent's reason to reach for a shell (attempt 003 paged a 2400-line file cleanly, no shell). Honest boundary note (case study + code comments): in THIS dev container the SDK tool allow/deny layer is defense-in-depth, not the trust boundary — a nested CLI as root under a parent session doesn't reliably gate built-ins. SPEC §10's boundary is OS process/user isolation; that hardening is the remaining Phase 2 exit item (docs/infra.md). What holds regardless: propose_patch is the only mediated write path (path-allowlist + git apply) and the ledger is append-only. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
84 lines
6.1 KiB
Markdown
84 lines
6.1 KiB
Markdown
# hotpath — profile-guided optimization agent
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> Working name. Rename freely; nothing depends on it.
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## Mission
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An agent that profiles real binaries and services, isolates hot paths, proposes optimizations, and accepts a change **only** when (a) behavioral-equivalence gates pass and (b) the benchmark improvement is statistically significant on trusted infrastructure. Output: verified performance deltas translated into ROI reports nobody can dispute.
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Full engineering spec: `SPEC.md`. Read it before starting any phase.
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## Non-negotiables (re-read every session)
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1. **No unverified performance claims.** A change without passing equivalence gates AND a significant bench delta does not exist. Discard it. Log it.
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2. **Measure before optimizing.** No patch is proposed until profile data identifies the hot path. Never trust a single benchmark run.
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3. **Cheap wins first, always.** Build flags → LTO → PGO → allocator swap → *then* code changes. Check the ledger before re-attempting any class of change on a target.
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4. **Equivalence gates are hard gates.** Changes touching floating-point ordering, concurrency primitives, or anything UB-adjacent are NEVER auto-accepted — verdict is `needs-human-review`.
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5. **Every attempt goes in the ledger**, including failures and rejections. Failures are future training data.
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6. **The agent never modifies the trust layer.** `crates/`, `config/`, `corpora/`, and upstream test suites are read-only to the agent. Patches may touch only allowlisted paths under `targets/<name>/`. See SPEC.md §10.
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7. **Sandbox everything.** Target code runs only inside no-network containers. Never on the host.
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8. **Statistical bar:** accept only if the bootstrap 95% CI lower bound of speedup ≥ threshold in `config/accept.toml` (default 2%), from interleaved A/B runs on the same pinned hardware.
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## Architecture map
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- `crates/bench-runner` — trust layer: containerized, CPU-pinned, interleaved A/B benchmarking with bootstrap confidence intervals and A/A self-tests
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- `crates/diff-test` — behavioral equivalence: upstream test suite + golden I/O replay + differential fuzzing of changed functions + sanitizers
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- `crates/ledger` — append-only SQLite record of every attempt: hypothesis, patch, gate results, bench deltas, verdict, cost
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- `crates/report` — ROI generator: cores saved × $/core-hr, latency percentile deltas, CIs, workload caveats printed on every number
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- `agent/` — Claude Agent SDK (Python) loop, prompts, tool definitions
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- `targets/` — vendored OSS targets for case studies (permissive licenses only)
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- `playbook/` — optimization classes, ordered, with preconditions and known risks
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- `results/` — generated reports and flamegraphs
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## Current phase
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**Phase 2 in progress — agent loop.** The unattended profile→hypothesize→patch→gated-verdict loop runs on comrak via the Claude Agent SDK (`agent/hotpath_agent/loop.py`, model claude-fable-5) over a stdio MCP server wrapping the seven harness tools. 3 audited attempts (phase2-comrak-001/002/003), all honest rejections, **0 false accepts**; the agent twice refused to fabricate an unreadable verdict (results/phase2/case-study-agent-loop.md). Shipped: async run_verdict + pollable read_verdict, windowed read_target_source. Exit-criteria gaps: an auto-accepted win (needs richer profiling to unlock more classes), and OS-level process/user isolation for the agent's tool boundary (SPEC §10; the SDK allow/deny layer is defense-in-depth only — see docs/infra.md). (Update this line as phases complete; exit criteria in SPEC.md §5.)
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## Commands
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Fill these in as the harness is built; keep them current:
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```
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just profile <target> # perf record + flamegraph for a target's benchmark workload
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just bench <target> <ref> # interleaved A/B: pristine baseline vs working tree
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just gates <target> # test suite + golden replay + diff-fuzz + sanitizers
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just verdict <target> # runs gates + bench, writes ledger row, prints verdict
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just report <run-id> # ROI report from ledger
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just aa <target> # A/A calibration run (must show null result)
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```
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Built so far (command-level, pre-target-integration):
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```
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just build / test / lint # trust-layer workspace: cargo build/test/clippy+fmt
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just aa [cmd] # A/A self-test of bench-runner on a shell command
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just compare <a> <b> # interleaved A/B of two shell commands, bootstrap CI
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just gates <target> # corpus pin + upstream tests + golden replay
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just pin-check <target> # verify corpus MANIFEST.sha256
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just calibrate <cmd> <out> # automated A/A + regression-injection calibration
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just verdict <t> <bin> ... # gates + bench vs pristine-rebuilt baseline + ledger row
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cargo run -p harnessd # agent IPC daemon: six-tool JSON surface (SPEC §3.5)
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```
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## Definition of done — one optimization attempt
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- [ ] Hypothesis logged in ledger *before* patching
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- [ ] Patch touches only allowlisted paths under `targets/<name>/`
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- [ ] Upstream test suite green
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- [ ] Golden replay byte-identical (or within the target's explicit FP tolerance policy)
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- [ ] Differential fuzz on changed functions: no divergence (60s or 10k iterations minimum)
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- [ ] ASan + UBSan clean; TSan if the patch touches anything threaded
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- [ ] Interleaved A/B bench passes the CI-lower-bound threshold
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- [ ] Ledger row written with verdict and full evidence
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- [ ] If FP-ordering / concurrency / UB-adjacent: verdict `needs-human-review`, never auto-accept
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An attempt that fails any gate is a **valid, complete outcome** — write the ledger row and move on. Do not iterate on a rejected patch more than twice without a new hypothesis.
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## Conventions
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- Rust workspace (edition 2021+) for all harness crates; `just` for task running
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- Python 3.11+ for `agent/`; Claude Agent SDK — verify current package name and API at https://docs.claude.com/en/docs/claude-code/overview before scaffolding
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- Every number shown to a human carries its confidence interval and workload description. No naked percentages, ever.
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- Commit style: `phase0:`, `bench:`, `gates:`, `agent:`, `playbook:` prefixes
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- When in doubt between shipping a feature and hardening measurement, harden measurement. The product is trust.
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