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 ivegamsft/basecoat --skill basecoat-helpgit clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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/ivegamsft/basecoat/basecoat-help)<a href="https://agentmods.dev/skills/ivegamsft/basecoat/basecoat-help"><img src="https://agentmods.dev/badge/skills/ivegamsft/basecoat/basecoat-help/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/ivegamsft/basecoat/basecoat-help"><img src="https://agentmods.dev/badge/skills/ivegamsft/basecoat/basecoat-help.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 | $0.00071 | $0.00368 |
| Opus 5 | $0.00036 | $0.00184 |
| Sonnet 5 | $0.00014 | $0.00074 |
| Haiku 4.5 | $0.00007 | $0.00037 |
Grade A, and why
basecoat-help 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 4d 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
BaseCoat Help
Answer /basecoat help (and help intent|agents|skills|workflows) from
generated catalogs. Do not invent names.
Workflow
- Read
docs/guides/basecoat-help.mdfor command shape and sample prompts. - Topic sources (load only what the user asked for):
- intents:
docs/guides/intent-prefixes.md - agents/skills:
docs/reference/prompt-library.md - workflows:
docs/guides/workflows-getting-started.mdanddocs/guides/workflows-reference.md - overloaded words:
docs/reference/glossary.md
- intents:
- Reply with a short table plus one ready-to-copy prompt per row.
- If the topic is unknown, list the four topics and stop.
Guardrails
- Reuse
prompt-library.md; do not duplicate asset lists in this skill. - Prefer
docs/guides/basecoat-help.mdsample prompts over improvising. - Do not start implementation from a help request.
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.
- 4d ago First seen · 40 lines · 71 tokens per session scan A abdf1083f2ed
basecoat-help is a skill published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed yesterday), licensed MIT. It adds 71 tokens to every session and 368 once invoked, about $0.0004 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 2026-09-05.
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