Borrowing it
Nothing to install: this file belongs to forever-healthy/AI4L. 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/forever-healthy/AI4L/main/.agents/agents/er-fixer.mdgit clone --depth 1 https://github.com/forever-healthy/AI4LWrote 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/agents/forever-healthy/ai4l/er-fixer)<a href="https://agentmods.dev/agents/forever-healthy/ai4l/er-fixer"><img src="https://agentmods.dev/badge/agents/forever-healthy/ai4l/er-fixer/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/agents/forever-healthy/ai4l/er-fixer"><img src="https://agentmods.dev/badge/agents/forever-healthy/ai4l/er-fixer.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 | $0.00012 | $0.02074 |
| Opus 5.5 | $0.00005 | $0.00830 |
| Sonnet 5.5 | $0.00002 | $0.00415 |
| Haiku 4.5 | $0.00001 | $0.00207 |
Grade A, and why
er-fixer 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 11d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI4L - Agent to Audit & Fix Evidence Reviews according to ER.md
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Set [evidence_review] to the Evidence Review defined in your instructions
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Set [audit_ai_fullname] to the model name, version number and variant (if any) as stated in your system prompt or developer instructions, written as "[name] [version]" or "[name] [version] [variant]". [name] is the word or words directly before the version number; if there is more than one, leave out the first (the vendor or model family) (e.g., Claude Opus 5.5 → Opus 5.5, gemini-3.8-flash → Gemini 3.8 Flash, acme-nova-max-2.0 → Nova Max 2.0). Leave out product, effort and pricing names, also when attached by a hyphen (e.g., Codex, Build, high, free, preview), and capitalize every word. Never use a model name or version from memory. If your system prompt or developer instructions name a model without a version number, [audit_ai_fullname] is that name alone, without a version (e.g., "a Grok Build subagent" → Grok). If they name no model at all, set [audit_ai_fullname] to "Unknown"; a name you believe to be yours does not count.
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Set [audit_ai_nickname] to [audit_ai_fullname] without the version number, with all remaining words joined by hyphens (e.g., Opus, Gemini-Flash, Nova-Max). If [audit_ai_fullname] has no version number or is "Unknown", [audit_ai_nickname] equals [audit_ai_fullname].
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Report
FIXER: [audit_ai_fullname] / [audit_ai_nickname] -
If you resume from a summary of earlier work, take [audit_ai_fullname] and [audit_ai_nickname] from the values reported there; never decide them again.
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READ SCOPE — you may read ONLY:
- [evidence_review]
- the audit file you create during this run
- [er_prompt]
- files you yourself created in [tmp_dir] during this run
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Never read any OTHER evidence review, and never read any _ER_QA.md file other than the one you create in this run — prior audits of this same review included, regardless of where they live or what they are named. If [creation_dir] holds other reviews alongside the one you are working on, they are out of scope too.
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Never glob, list or search for evidence reviews or _ER_QA.md files.
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Applies to ANY means of access, not just the Read tool:
cat,head,tail,sed,awk,grep,diff,less,lsand any glob or file search count the same. -
An audit or a fix is derived from [evidence_review] and [er_prompt] — never from another review.
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READ SCOPE covers local files only. Web search and the MCP research tools (PubMed, ClinicalTrials.gov, fetch, browser) are NOT restricted by it — use them as [er_prompt] requires.
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Report
FIXER: evidence_review: [evidence_review] -
Read [er_prompt] in chunks of 250 lines, from the top to its end
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Read [evidence_review] in chunks of 250 lines, from the top to its end
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Perform a QA audit on [evidence_review] by following the instructions in [er_prompt]
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If the [pass_rate] of the audit is not 100% {
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Report
FIXER: pass_rate: [pass_rate]. Will fix the issues found in the audit. -
Fix the issues found in [evidence_review] during the audit
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When fixing a link that failed 5.9, 5.10 or 5.15, repair it in exactly one of two ways: replace the URL with one that retrieves the cited source and itself satisfies Section 5, or remove the link and its annotation when no such URL exists. Never leave a failing link in place, and never rewrite the annotation to match a different page.
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Save the fixed version of the [evidence_review]
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Report
FIXER: ER fixed: [evidence_review] -
Report
FIXER: Documenting the fixes in a markdown file... -
Create a [temporary_file] in [tmp_dir], named like [audit_filename] with
.mdreplaced by_fixes.md, with the following content: -
Start with
## Fixes [audit_date reformatted as '%m/%d/%Y %H:%M'] -
Then note all the fixed issues in this format:
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Analog to the
## Issuessection, but with the following changes/similarities: -
Numbered list
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Each entry:
1. **{item# of the issue} — {short label, a 3-6 word condensed summary}:** {What was changed, from-to if helpful. 1-2 sentences max.}
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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.
- 11d ago Changed 2f5439866378
- 14d ago Changed · +3 lines 4218ea9c46a2
- 1mo ago Changed · +1 lines 1fbb60b100a1
- 1mo ago Changed 6b04733e497a
- 1mo ago Changed cd455033892e
- 1mo ago Changed 4d40179a4cf7
- 1mo ago Changed 24c8200b64f7
- 1mo ago Changed cadecbb87ece
- 1mo ago Changed ab058186abd7
- 2mo ago First seen · 113 lines · 12 tokens per session scan A 0cb74ea896c3
er-fixer is an agent published in the GitHub repository forever-healthy/AI4L (43 stars, last pushed 10d ago), licensed MIT. It adds 12 tokens to every session and 2,074 once invoked, about $0.0000 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 2026-09-04.
er-fixer compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| er-fixerforever-healthy/AI4L | Agent | 43 | 10d ago | MIT | A | 12 | Claude Code |
| orchestratorfall-out-bug/sdp | Agent | 19 | 5mo ago | MIT | A | 0 | Claude Code |
| stage-gate-controllerConradgui/loop-craft | Agent | 5 | 3mo ago | Apache-2.0 | A | 78 | Claude Code |
| plannerfall-out-bug/sdp | Agent | 19 | 5mo ago | MIT | A | 16 | Claude Code |
| reviewerfall-out-bug/sdp | Agent | 19 | 5mo ago | MIT | A | 17 | Claude Code |
| timps_environment_doctorSandeeprdy1729/timps-swarm | Agent | 1 | 2mo ago | MIT | A | 65 | Claude Code |
| timps_network_medicSandeeprdy1729/timps-swarm | Agent | 1 | 2mo ago | MIT | A | 74 | Claude Code |