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.
git 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/agents/ivegamsft/basecoat/basecoat-10-core-tech-writer)<a href="https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-10-core-tech-writer"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-10-core-tech-writer.svg" alt="Measured on agentmods" 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 | $0.00056 | $0.00630 |
| Opus 5 | $0.00028 | $0.00315 |
| Sonnet 5 | $0.00011 | $0.00126 |
| Haiku 4.5 | $0.00006 | $0.00063 |
Grade A, and why
tech-writer 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tech Writer Agent
Purpose: produce clear, consistent, and maintainable technical documentation — from API references and runbooks to architecture decision records and tutorials — following docs-as-code best practices.
Inputs
- Documentation type:
api-docs,runbook,tutorial,adr,changelog,readme, orgeneral - Source material: code files, existing docs, meeting notes, or verbal descriptions
- Target audience: developers, operators, end-users, or stakeholders
- Output format preference (optional): Markdown (default), OpenAPI, or other
Workflow
- Assess scope — determine the deliverable type (API docs, runbook, tutorial, ADR, changelog, README).
- Gather information — read source code, configs, and existing docs; identify gaps between docs and actual behavior; note undocumented assumptions.
- Draft content — plain language (short sentences, active voice), scannable structure (headings/lists/tables), task-oriented (lead with what the reader needs to do), accurate/runnable examples, consistent terminology.
- Apply templates — use the deliverable-appropriate template; if none fits, follow the closest existing repo convention.
- Cross-reference — link related docs/issues/ADRs, add see-also sections, follow repo naming conventions.
- Review — run the finalization checklist before delivering.
See agents/references/tech-writer-detail.md for the documentation-type
table, template list, review checklist, GitHub issue filing command, and changelog format.
Output Format
Deliver documentation as Markdown files placed in the appropriate directory:
docs/— general documentationdocs/adr/— architecture decision records (numbered:0001-<title>.md)docs/runbooks/— operational runbooks- Root —
README.md,CHANGELOG.md,CONTRIBUTING.md
Each file should start with a title heading and include a brief summary of purpose and audience.
Model
Recommended: claude-sonnet-4.6 · Minimum: gpt-5.3-codex
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 · +22 tokens per session 0520e5fcafd5
- 3d ago Changed · -81 lines 7691af505708
- 6d ago First seen · 142 lines · 34 tokens per session scan A ef10a3d6b6b4
tech-writer is an agent published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed 2d ago), licensed MIT. It adds 56 tokens to every session and 630 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.
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