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 skills/asteasolutions/ai-toolkit/agentic-loopnpx skills add asteasolutions/ai-toolkit --skill agentic-loopgit clone --depth 1 https://github.com/asteasolutions/ai-toolkitWhat 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 | $0.00038 | $0.00923 |
| Opus 5 | $0.00019 | $0.00462 |
| Sonnet 5 | $0.00008 | $0.00185 |
| Haiku 4.5 | $0.00004 | $0.00092 |
Grade A, and why
agentic-loop 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic loop
The developer's attention is the scarce resource, and this loop spends it at the specification rather than during execution. They approve what is to be built; the work is then written, verified, and judged by a reviewer in a fresh context, and they hear from you once.
Reach for it when the goal is well enough understood to specify. When the developer needs to hold the change in their head as it happens, this is the wrong tool — it deliberately takes that away.
Invariant: one scheduled interruption. The front gate below is the only planned stop. After it, the loop reports when it is done — or halts and reports when it cannot proceed without guessing.
Invariant: this skill never writes code. It gates and hands off. Implementation belongs to
implementer, judgement toreviewer, sequencing toorchestrator.
1. Front gate
Everything this task produces lives in one run directory: {{WORK_DIR}}/<goal-slug>/. Nothing about the task is written anywhere else, and no other task writes into it — one directory the developer can open, read in order, and delete when the task is done.
Slugify the goal and look for that directory first. It already exists with a spec → this is a resume: read the spec and progress.md, and continue from the first slice that has not landed. Do not re-derive what the record already holds.
Otherwise, produce two things in this conversation, together:
- A spec with numbered clauses — each one a single checkable statement about behaviour after the change. Clauses are what the reviewer renders a verdict against, so a clause nobody can check is a clause nobody will enforce. If a spec-writing skill is installed, invoke it and number the criteria it produces; otherwise draft the spec here.
- An ordered slice list — each slice independently verifiable, and each naming the clauses it satisfies.
Ask about anything you would otherwise guess at, and resolve it before the gate. Every clause of the spec is a thing three agents will act on unattended; an ambiguity that survives this gate is one they will resolve without the developer.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 53 lines · 38 tokens per session scan A 202f53ad5c4b
agentic-loop is a skill published in the GitHub repository asteasolutions/ai-toolkit (5 stars, last pushed 6d ago), licensed MIT. It adds 38 tokens to every session and 923 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 2026-08-31.
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