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 Stahl-G/briefloop --skill entry-skillgit clone --depth 1 https://github.com/Stahl-G/briefloopWrote 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/stahl-g/briefloop/entry-skill)<a href="https://agentmods.dev/skills/stahl-g/briefloop/entry-skill"><img src="https://agentmods.dev/badge/skills/stahl-g/briefloop/entry-skill/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/stahl-g/briefloop/entry-skill"><img src="https://agentmods.dev/badge/skills/stahl-g/briefloop/entry-skill.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 | $0.00062 | $0.02012 |
| Opus 5 | $0.00031 | $0.01006 |
| Sonnet 5 | $0.00012 | $0.00402 |
| Haiku 4.5 | $0.00006 | $0.00201 |
Grade A, and why
wikiskill 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 today.
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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WikiSkill
Help the user improve a recurring agent task through experience. Use the user's current agent, chosen model and normal tools. WikiSkill owns the work requests, records, scores and retained skill versions; it does not select a model or change host permissions.
Start with the user's intent
- Remember feedback: save it with
wikiskill feedback; do not start an improvement run merely because a note was added. - Improve a skill: identify the task examples, evaluation criterion, current skill if any, and the user's intended effort/budget. Reuse information already provided. Begin with one round unless the user requests more; there is no hard sample or round cap.
- Resume: read
wikiskill status, then usewikiskill nextin the existing workspace. Do not initialize a duplicate run. - Check only: use
wikiskill statusand existing artifacts; do not start more work. - Use the result: export the retained skill. Install or replace an existing skill when the user has authorized that destination.
Read workflow commands and formats when preparing tasks or operating the loop. Use wikiskill capabilities to discover the installed interfaces. If the package is missing, use the user's selected checkout or the official repository. Prefer an existing project virtual environment; otherwise create a project-local venv and use its Python and wikiskill executables. Do not default to modifying the system/global Python environment. Installation executes package build code, so inspect unfamiliar sources first. The product path works without a Codex CLI account.
If another skill-improvement tool such as skill-evolve is installed, compare its description rather than assume the tools are equivalent. Keep ordinary creation/rewriting with the user's chosen editor. Choose WikiSkill for the task-score-Wiki-validation cycle, or when the user names WikiSkill. Do not run two improvement controllers for the same task or recommend uninstalling the other skill merely because both are present.
What ships with it
3 files 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.
- today First seen · 75 lines · 62 tokens per session scan A 9e18ac596b96
wikiskill is a skill published in the GitHub repository Stahl-G/briefloop (9 stars, last pushed today), licensed MIT. It adds 62 tokens to every session and 2,012 once invoked, about $0.0003 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 2026-09-12.
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