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 theafh/ai-modules --skill task_checkgit clone --depth 1 https://github.com/theafh/ai-modulesWrote 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/theafh/ai-modules/task_check)<a href="https://agentmods.dev/skills/theafh/ai-modules/task_check"><img src="https://agentmods.dev/badge/skills/theafh/ai-modules/task_check/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/theafh/ai-modules/task_check"><img src="https://agentmods.dev/badge/skills/theafh/ai-modules/task_check.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 | $0.00077 | $0.02252 |
| Opus 5.5 | $0.00031 | $0.00901 |
| Sonnet 5.5 | $0.00015 | $0.00450 |
| Haiku 4.5 | $0.00008 | $0.00225 |
Grade A, and why
task_check 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 yesterday.
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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
task_check
<task_check_skill>
<when_to_activate> Activate when the user wants a single task's readiness judged before building:
- "Is
<task>ready?" / "check this task before I build it" / "assess this task's readiness." - "Will a one-shot implementer get this right?"
Route elsewhere when the user wants to write a task (task_create or the base task skill), automatically repair a task until this gate reports ready (task_auto_check), choose what to work on next (task_select), do the implementation work (task_implement), verify a believed-done task against the codebase (task_audit), close a task (task_finish), or health-check the whole tree (task_fix). The crisp line: task_check judges one task's readiness before building; task_auto_check is the opt-in loop that edits the task and reuses this gate; task_select ranks eligible backlog candidates; task_audit verifies one task's claimed completion after building.
</when_to_activate>
<path_resolution>
The base task skill's discover_tasks.sh ships in scripts/ next to that skill's SKILL.md, not next to this one. After reading the base SKILL.md (per <authority>), resolve the script's absolute path by combining the directory you loaded it from with scripts/<script-name> and invoke that absolute path, never a bare scripts/..., which resolves against the current working directory (the target project) rather than the skill. If the first invocation reports a missing file, re-resolve the absolute path once before treating the script as failed.
</path_resolution>
Assess against the base task skill's <readiness_checklist>, in its order: the charter and structural checks, then the premise, approach-fitness, and Interaction scan checks against the codebase, then the content lens item by item. The checklist lives once in the base skill as the family's single source; apply it from there rather than from a copy here. Class every verified finding with the checklist's Blocking bar: a blocking finding is a readiness issue and belongs in ## Issues, and a note belongs in ## Notes. Class by the bar's test alone: a finding whose literal reading produces one of the bar's four wrong results blocks however small its fix, and a finding with no nameable wrong result is a note however easy its 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.
- yesterday Changed · +2 lines 19ca44fc763f
- 15d ago Changed f0c876bdecd4
- 17d ago Changed · +2 lines e0eebad1f68d
- 1mo ago Changed e3dd17ee4fb6
- 1mo ago First seen · 77 lines · 77 tokens per session scan A db2c77c9a7d1
task_check is a skill published in the GitHub repository theafh/ai-modules (38 stars, last pushed today), licensed MIT. It adds 77 tokens to every session and 2,252 once invoked, about $0.0003 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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