Borrowing it
Nothing to install: this file belongs to AHepi/DeepReason. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AHepi/DeepReason/main/.claude/skills/dr-implement-fix/SKILL.mdgit clone --depth 1 https://github.com/AHepi/DeepReasonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ahepi/deepreason/dr-implement-fix)<a href="https://agentmods.dev/skills/ahepi/deepreason/dr-implement-fix"><img src="https://agentmods.dev/badge/skills/ahepi/deepreason/dr-implement-fix/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ahepi/deepreason/dr-implement-fix"><img src="https://agentmods.dev/badge/skills/ahepi/deepreason/dr-implement-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.01216 |
| Opus 5.5 | $0.00016 | $0.00486 |
| Sonnet 5.5 | $0.00008 | $0.00243 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
dr-implement-fix scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implement the fix
Input: an approved FIX.md. Output: one commit containing the fix, its regression test, and any fixture updates FIX.md authorized — nothing else.
Procedure
-
Touch only FIX.md's change sites. If implementation reveals a needed site FIX.md missed, STOP: amend FIX.md first (one commit), then continue. Silent scope growth is the failure mode this workflow exists to prevent.
-
Write the regression test first, converting the REPRO artifact: it fails before your change, passes after. Its docstring names the live run/record that motivated it (e.g. "Regression (selfstudy run-9175f0ec): ..."), so the next reader can find the evidence. Build it to
dr-execute-step's "Durable tests, checks, and probes" rules — committed evidence only, meaning over form, mutation-proved, wall-clock scrubbed recursively, absence-tolerant — so it survives repo changes and fails only when the defect returns. -
Apply the code change. Comments state the constraint the code cannot show ("compare by handle index, not mapping order: canonical JSON sorts keys"), never the change's history or your reasoning.
-
Run outward rings, stop at first failure:
pytest <regression test> -x -q pytest <the changed subsystem's test files> -q pytest tests/ -q -n 4 # full gate, ~8 minThe full gate must report 0 failed. A pre-existing failure you did not cause: stop, report, do not "fix it while you're there." If FIX.md's change sites touch the packaging surface (pyproject entry points, CLI commands, MCP tools/schema, wheel layout), one more ring the gate does not run:
python scripts/wheel_smoke.py, with its pinned expectations updated in this same commit. -
A gate failure caused by your change is information: if a fixture depended on the defective behavior (FIX.md predicted it), update the fixture minimally so it exercises what the test actually guards; if the failure is NOT predicted by FIX.md, your fix is wrong — revert to the last green state and return to the orchestrator for re-diagnosis. Never weaken an assertion to green.
-
If a live run root is needed for the next phase and the identity is occupied: retire it — procedure canonical in
dr-drive-harness§3 (retire by rename, commit the rename FIRST as its own commit). -
Update the map in THIS commit — see "Map obligations" below.
-
Before committing, run the mechanized budget gate against FIX.md's Estimated-diff ceiling — the same instrument
dr-execute-stepuses for Family-2 steps, so this check can no longer be an eyeballedgit diff --statcompare:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 98 lines · 40 tokens per session scan A 8b0999634efd
dr-implement-fix is a skill published in the GitHub repository AHepi/DeepReason (141 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 1,216 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
4-phase root cause debugging: understand bugs before fixing.
observability-langsmith
LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.
reenable-test
Guide for investigating, fixing, verifying via TDD, and re-enabling disabled or flaky Chromium tests (C++, Android Java, or WebUI). Use this skill when asked to deflake, fix, or re-enable a disabled or flaky test case, or to verify post-submit stability of a re-enabled test. Don't use for disabling a failing test…
experimental-code-coverage-local-debugger
Runs code coverage locally via Universal Test Runner (UTR) or helper scripts, mimicking LUCI trybots. Activate when CQ tryjobs fail or underreport coverage, to test local GN/recipe repairs before uploading, or to debug hermetic crashes.
verify-omnigent
Drive Omnigent the way a user does and prove a behavior with recorded evidence, using an isolated server, runner, and mock model plus a feature map of every user entry point. Load before reproducing a user-facing bug, before claiming a fix works, or when reviewing whether a change covered every surface (session vs.…
cli-e2e
Write, modify, or debug Docker-based Composio CLI end-to-end tests under ts/e2e-tests/cli, including binary invocation, fixture isolation, output assertions, and package manifests. Use for CLI E2E test suites only; use cli-command for CLI source implementation.