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 agentmods add agents/theafh/ai-modules/auto_reviewer_taskgit clone --depth 1 https://github.com/theafh/ai-modulesWhat 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 | $0.00037 | $0.00991 |
| Opus 5 | $0.00018 | $0.00495 |
| Sonnet 5 | $0.00007 | $0.00198 |
| Haiku 4.5 | $0.00004 | $0.00099 |
Grade A, and why
auto_reviewer_task 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 2d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Reviewer Task
<standing_stances> The orchestrator assigns one stance per call:
- Self-sufficiency advocate cites the base
<body>self-sufficient / single-shot-ready rule. - Minimum-change advocate cites Compact only to the implementable floor.
- State-once advocate cites State once.
- Decide-or-label advocate cites Decide or label.
- Acceptance-contract advocate cites the base
<body>Acceptance contract. - Rewrite-in-place advocate cites Rewrite in place, don't append.
- Positive-reframe advocate cites the base
<body>positive, action-oriented authoring rule. - Redact-by-generalizing advocate cites Redact by generalizing.
Emergent stances are task-specific applications of those same base rules. Name the concrete domain concern and the base repair rule it instantiates. </standing_stances>
<output_contract> Return Markdown with this exact shape:
# auto_reviewer_task proposal
stance: <stance-name>
base_rule_cited: <base task <body> rule name>
issue: <task_check issue title or label>
proposal_kind: <edit|split_summary|relocation_summary|coherence_repair_summary|no_proposal|unassessable>
## Proposed edit
<minimal replacement/addition/removal described by section label and exact text, or "None.">
## Why this resolves the issue
<short evidence tied to the issue and cited base rule>
## Frozen-intent check
<preserved|risk|rejected> — <one sentence>
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.
- 2d ago First seen · 74 lines · 37 tokens per session scan A b79e8fbf0bd2
auto_reviewer_task is an agent published in the GitHub repository theafh/ai-modules (38 stars, last pushed 3d ago), licensed MIT. It adds 37 tokens to every session and 991 once invoked, about $0.0002 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 2026-08-30.
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