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 causify-ai/helpers --skill auto_task.criticizegit clone --depth 1 https://github.com/causify-ai/helpersWrote 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/causify-ai/helpers/auto_task.criticize)<a href="https://agentmods.dev/skills/causify-ai/helpers/auto_task.criticize"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/auto_task.criticize/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/causify-ai/helpers/auto_task.criticize"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/auto_task.criticize.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 | $0.00015 | $0.00500 |
| Opus 5.5 | $0.00006 | $0.00200 |
| Sonnet 5.5 | $0.00003 | $0.00100 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
auto_task.criticize 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 1mo 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
Goal
- The user will pass you a file
<FILE>(e.g.,tasks.md) or a GitHub issue number<GITHUB_ISSUE_NUM> - You will read carefully the passed content and make sure both the problem and the solution is clear and complete
Workflow
Read Context
- Read the content of the plan (file or GitHub issue)
- Analyze the problem and the solution, reviewing it carefully
Create a Plan, If Needed
-
When analyzing the problem, make sure to understand which repos are affected by the change, since this influences creating a PR for multiple repos
- Update the
* Repo:checklist in.claude/templates/auto_task.template.md, following.claude/skills/auto_task.rules.mdsection "Multi-Repo Issues, Branches, and PRs" - When more than one repo is checked, confirm each
PR<NUM>block in "Solution" states which repo it targets: an unlabeledPR<NUM>for a multi-repo task is an unclear plan (see "Ask for Clarification Before Executing an Unclear Plan" in.claude/skills/auto_task.rules.md) - Do not add or edit a
## Companion PRssection:git_create_issue_and_branch.pygenerates it automatically once PRs exist, per.claude/skills/auto_task.rules.md"Multi-Repo Issues, Branches, and PRs"
- Update the
-
If the task is not perfectly clear, follow
.claude/skills/auto_task.rules.mdsection "Ask for Clarification Before Executing an Unclear Plan"
Output Results
- Follow the rules in
.claude/skills/auto_task.rules.md - The output is a file in the format
.claude/templates/auto_task.template.md
Conventions
- Follow
.claude/skills/coding.rules.mdwhen writing code - Follow
.claude/skills/testing.rules.mdwhen writing testing code
Verification
- The problem statement is clear and unambiguous
- The proposed solution is clear and unambiguous
- Any needed clarification was requested before the task moves to execution
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.
- 1mo ago Changed · +2 lines c46f07d63981
- 1mo ago Changed · +22 lines ddb716a6beb6
- 1mo ago Changed · +3 lines · +6 tokens per session a492611734ba
- 1mo ago First seen · 26 lines · 9 tokens per session scan A 4a24ff4d3f30
auto_task.criticize is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 15 tokens to every session and 500 once invoked, about $0.0001 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 2026-08-30.
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