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 ManceRayder42/jarvis-os --skill wiki-articlegit clone --depth 1 https://github.com/ManceRayder42/jarvis-osWrote 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/mancerayder42/jarvis-os/wiki-article)<a href="https://agentmods.dev/skills/mancerayder42/jarvis-os/wiki-article"><img src="https://agentmods.dev/badge/skills/mancerayder42/jarvis-os/wiki-article/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/mancerayder42/jarvis-os/wiki-article"><img src="https://agentmods.dev/badge/skills/mancerayder42/jarvis-os/wiki-article.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 | $0.00070 | $0.00510 |
| Opus 5 | $0.00035 | $0.00255 |
| Sonnet 5 | $0.00014 | $0.00102 |
| Haiku 4.5 | $0.00007 | $0.00051 |
Grade A, and why
wiki-article 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 12d 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
Wiki article
When this is required
If you grep, or spawn Explore-style agents, to learn the structure of an active project — and that project lives inside the hub (<hub>/<project>/) — write a wiki article before running /done. The reasoning: that discovery cost real tokens and real time; without a durable record, the next session repeats the same search from scratch, and that cost compounds every time. A short article converts one-time discovery into standing knowledge.
Skip this for shallow lookups (a single grep, one file read) — see "Length" below for the anti-fabrication guard that covers that case.
Template
---
topic: <topic>/<subtopic>
last-updated: YYYY-MM-DD
sources:
- <file paths you actually read>
---
# <Component / Concept>
## What it is
2–3 sentences, concrete.
## When to read this article
- Bullet list of agent questions it answers
## How it works
Concrete mechanism with file:line references.
## Inputs / Outputs
- Inputs: ...
- Outputs: ...
## Failure modes
1. <mode> — detected by <symptom>, root cause <X>
## Code references
- `path/to/file:line` — what's there
## Related
- [[../other-article]]
Save + register
- Save to
<hub>/wiki/<project>/<topic>/<article>.md. - Add it to that project's
<hub>/wiki/<project>/index.md(create the index if this is the first article for the project). - Mention it in the session note's "Work done" section.
- Then
/done— its commit step picks up anything dirty under<hub>/wiki/automatically.
Length
200–400 words. If discovery was shallow (1–2 files read, not enough to write 200 words honestly), do NOT fabricate — append a 5-line "what's missing for a wiki article" stub to the topic's index.md instead, so the next agent knows where to start.
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.
- 12d ago First seen · 59 lines · 70 tokens per session scan A 47b9d7d541b9
wiki-article is a skill published in the GitHub repository ManceRayder42/jarvis-os (5 stars, last pushed 7d ago), licensed MIT. It adds 70 tokens to every session and 510 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 2026-08-31.
Other skills, from other repositories
confidence-gate
When you're about to claim success ("fixed", "done", "works", "passing tests") at the end of a turn, verify the claim is backed by actual evidence in this session. presence's Stop hook will flag a success claim that has no recent test/build pass behind it. Be aware of this gate and either run the verification, or…
evolve-lite:save-trajectory
Save the current conversation as a trajectory JSON file in OpenAI chat completion format for analysis and fine-tuning.
github-pr-creation
Creates GitHub Pull Requests with automated validation and task tracking. Use when user wants to create PR, open pull request, submit for review, or check if ready for PR. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels. NOTE - for merging existing…
test-run
Run plugin test suites in this monorepo and report a concise pass/fail summary. Optional plugin slug arg; without arg, runs all plugins under plugins/.
cco-tools
Show what tools actually cost in tokens — learned per-tool averages from observed results, replacing the hardcoded MCP/Agent guesses.
graphify
Use when the user invokes /graphify or asks to build, update, or query a knowledge graph from a folder of files (code, docs, papers, notes, images). Triggers: 'map this codebase', 'graph my notes', 'what is connected across these files', 'community detection', 'GraphRAG', incremental graph update, Neo4j/SVG/GraphML…