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 resolve-ai-oss/resolve-ai-plugins --skill apply-fixgit clone --depth 1 https://github.com/resolve-ai-oss/resolve-ai-pluginsWrote 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/resolve-ai-oss/resolve-ai-plugins/apply-fix)<a href="https://agentmods.dev/skills/resolve-ai-oss/resolve-ai-plugins/apply-fix"><img src="https://agentmods.dev/badge/skills/resolve-ai-oss/resolve-ai-plugins/apply-fix.svg" alt="Measured on agentmods" 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 | $0.00078 | $0.00428 |
| Opus 5 | $0.00039 | $0.00214 |
| Sonnet 5 | $0.00016 | $0.00086 |
| Haiku 4.5 | $0.00008 | $0.00043 |
Grade A, and why
apply-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 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
Apply Fix from Resolve Findings
Bridges Resolve's production-side diagnosis to local code edits.
Workflow
- Pick the target finding. Usually a root-cause theory from
get_investigation. If multiple, ask the user which to address. - Read the theory and its citations via
read_fileon the theory's path and its citation paths. Citations are log lines, queries, traces — the supporting evidence. - Gather what's missing for a code change. Theories describe what's broken in production, not what to write locally. You fill that in by reading local code: which file owns the relevant path, what the current implementation does, where the change goes.
- Optionally, send a code-shaped question back to Resolve via
askfor context you can't infer locally. Don't block on it — work in parallel. - Locate the relevant local code with Grep/Read.
- Propose the fix: the theory addressed, the citations supporting it, the files being changed, why the change should work. Then implement.
- Open a PR. If a PR-creation skill is available, load and use it to open the pull request; otherwise follow the repo's normal PR flow. Land the work as a reviewable PR, not a dirty working tree.
- Optionally call
steer_investigationwith "Applied mitigation: " so the investigation records the fix.
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 · 24 lines · 78 tokens per session scan A 7b2986db0509
apply-fix is a skill published in the GitHub repository resolve-ai-oss/resolve-ai-plugins (4 stars, last pushed 13d ago), licensed Apache-2.0. It adds 78 tokens to every session and 428 once invoked, about $0.0004 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 2026-08-31.
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