Borrowing it
Nothing to install: this file belongs to alonf/specrew. 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/alonf/specrew/main/.squad/skills/resume-state-repair/SKILL.mdgit clone --depth 1 https://github.com/alonf/specrewWrote 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/alonf/specrew/resume-state-repair)<a href="https://agentmods.dev/skills/alonf/specrew/resume-state-repair"><img src="https://agentmods.dev/badge/skills/alonf/specrew/resume-state-repair/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/alonf/specrew/resume-state-repair"><img src="https://agentmods.dev/badge/skills/alonf/specrew/resume-state-repair.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 | $0.00024 | $0.00500 |
| Opus 5 | $0.00012 | $0.00250 |
| Sonnet 5 | $0.00005 | $0.00100 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
resume-state-repair 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 7d 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.
What it actually says
Context
Use this when a resume or recovery helper reads both state.md and plan.md, and stale execution metadata could cause the workflow to skip incomplete tasks after an interruption.
Patterns
- Treat the task table in
plan.mdas the authority for which tasks are stillplanned,in-progress,needs-rework,blocked, ordone. - Let
state.mdcarry only the volatile execution details that may be newer than the plan table, especially active in-progress tasks. - Rebuild
Tasks Remainingfrom authoritativeplannedtasks instead of trusting a stale comma-separated list. - Preserve or infer
In Progressfromstate.mdfirst, then fall back to task-table statuses when state metadata is missing. - Rewrite repaired metadata before appending or refreshing any managed resume report so the artifact itself becomes the recovery output.
Examples
state.mdsaysTasks Remaining: T-003, butplan.mdstill showsT-002andT-003as planned. RepairTasks Remaining, setT-002in progress on continue, and keepT-003queued.state.mdis missingIn ProgressandUpdated. Reconstruct them from the task table and write the repaired fields during resume.
Anti-Patterns
- Trusting a stale
Tasks Remaininglist over the live task table. - Leaving repaired resume results only in JSON output while
state.mdstays stale. - Using task-table order alone as the execution order when the iteration can complete tasks out of order.
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.
- 7d ago First seen · 41 lines · 24 tokens per session scan A 95e6f564d4d7
resume-state-repair is a skill published in the GitHub repository alonf/specrew (54 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 500 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
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