Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add chan4lk/specclaw --skill reviewgit clone --depth 1 https://github.com/chan4lk/specclawWrote 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/chan4lk/specclaw/review)<a href="https://agentmods.dev/skills/chan4lk/specclaw/review"><img src="https://agentmods.dev/badge/skills/chan4lk/specclaw/review/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/chan4lk/specclaw/review"><img src="https://agentmods.dev/badge/skills/chan4lk/specclaw/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00043 | $0.01115 |
| Opus 5.5 | $0.00017 | $0.00446 |
| Sonnet 5.5 | $0.00009 | $0.00223 |
| Haiku 4.5 | $0.00004 | $0.00112 |
Grade A, and why
review 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 today.
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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
specclaw-review: the local review loop
The loop runs on this machine. Rounds are cheap model calls, so the build server never runs a review round. You push once, after the verdict is clean.
Tools: the specclaw-review MCP server (review_run, review_verdict, memory_query…), or the
specclaw-review CLI. Both run the same code. Never read .specclaw/review-memory/ directly. Use
memory_query.
The loop
- Round 1, the whole change:
specclaw-review run --change <change>.- Exit 0: clean. Go to step 4.
- Exit 1: blocker/major findings are open. Go to step 2.
- Exit 3: the review did not run. Report the error and stop. Never treat it as clean.
- Exit 4: escalate. The same finding survived two fixes. Stop patching and do step 3.
- Fix by class, not by case. For each blocker or major:
- Find every variant: other spellings and locales, every caller, every second copy of the logic.
memory_querywith the touched files shows what this repo has already been bitten by. - Fix them all in one change. Prefer a structural fix (a closed vocabulary, one shared function, an explicit "not run" state) over another special case.
- Add a table-driven variant test that fails without the fix: the named case plus at least two more.
- Run the project's tests, then commit. Do not push.
- Re-review only what changed:
specclaw-review run --change <change> --since <head of the previous round>. The round file (review/round-<n>.json) recordshead. Code merged from the base branch is excluded automatically. - Repeat until a round exits 0. There is no round cap. Minors never trigger another round: they land
in
follow-ups.md.
- Find every variant: other spellings and locales, every caller, every second copy of the logic.
- Escalation (exit 4). Tell the user which finding repeats and propose a redesign of that part. Continue only on their decision.
- Final pass:
specclaw-review run --change <change> --final. This is the whole change, on the stronger model.- Exit 1: go back to step 2.
- Exit 0:
specclaw-review verdict --change <change>must exit 0. That means clean, with the final pass at HEAD.
- Commit the round records (
.specclaw/changes/<change>/review/,follow-ups.md) and the memory file (git add .specclaw). Then push once:/specclaw:pr.
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.
- today First seen · 80 lines · 43 tokens per session scan A 3714cc952ce7
review is a skill published in the GitHub repository chan4lk/specclaw (13 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 1,115 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 2026-10-17.
Other skills, from other repositories
review-spec
A workflow for comparing an existing feature specification with the project's review checklist and implementation. It looks for missing requirements, differences between documented screens and actual screens, and lessons from rejected submissions.
loki-mode
An autonomous software factory that knows what it is supposed to deliver, and proves it did. Use when the user says Loki Mode or asks to build, fix or verify software autonomously.
next-steps
Have the Product Owner survey the project's current state — shipped features, in-flight work, open findings, standing goals — and propose one concrete next feature ready to hand to /story-time or /spark. Use when the user has no idea in hand and asks "what should we build next", when a loop just closed and the next…
increment
Start the Act phase of the SPARK loop: build the increment strictly following the approved plan, task by task, with progress tracked in the plan. Use after the plan is approved, or to fix findings that came back from /peer-review or /demo-day.
checkpoint-mode
Pause for review every N tasks - selective autonomy pattern.
loki-mode
Launch Loki Mode autonomous SDLC agent. Handles PRD-to-deployment with minimal human intervention. Invoke for multi-phase development tasks, bug fixing campaigns, or full product builds.