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 dougstanford/living-manual --skill manualgit clone --depth 1 https://github.com/dougstanford/living-manualWrote 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/dougstanford/living-manual/manual)<a href="https://agentmods.dev/skills/dougstanford/living-manual/manual"><img src="https://agentmods.dev/badge/skills/dougstanford/living-manual/manual/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/dougstanford/living-manual/manual"><img src="https://agentmods.dev/badge/skills/dougstanford/living-manual/manual.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 | $0.00107 | $0.03747 |
| Opus 5 | $0.00053 | $0.01873 |
| Sonnet 5 | $0.00021 | $0.00749 |
| Haiku 4.5 | $0.00011 | $0.00375 |
Grade A, and why
manual 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 11d 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 — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The living manual
One HTML file, self-contained, brand-styled, interactive: clickable headings file notes that become tickets, roadmap previews show planned changes, a glossary explains novel concepts on first use, and readers rearrange the manual by dragging its contents or correct its prose in place. The browser keeps a reader's order and their edits; an optional payload makes either one committed. This skill builds it once, then keeps it matched to the released code.
All prose you generate follows reference/writing-style.md in this
plugin. Read it before writing any manual content. It is binding.
Token discipline: the scripts in scripts/ exist so you never do their
work by hand. Run them, read their compact output, act on it. Do not
re-read the whole codebase on update runs; stale.sh tells you exactly
what changed.
$LM below is the plugin root. This file lives at
$LM/skills/manual/SKILL.md, so resolve it from the path this skill
loaded from.
Every question you ask during setup must be answerable from what is on the user's screen. Print the thing you are asking about (the feature map, the palette and its proposed roles, the tracker's projects, labels, and milestones) in your reply first, then ask. Answer choices never reference content the user has not been shown.
Every invocation starts the same way
sh $LM/scripts/state.sh
Branch on the JSON: configured: false → setup flow. Otherwise →
update flow (or the specific request the user made).
Setup flow (first run)
Work through these in order. Each step ends with something written to disk, so an interrupted setup resumes cleanly (state.sh shows what exists).
1. Orient to the codebase.
Run sh $LM/scripts/inventory.sh <repo-root>. From its output plus the
README and any changelog/roadmap docs, build the feature map:
user-facing surfaces and the shipped features on each. Read the main UI
entry point and each surface component; the manual documents what users
experience, so ground every section in the code that renders it.
Print the full map in your reply (a plain nested list: surface →
features), then ask the user to confirm or correct it — missing
features, wrong groupings, things that aren't user-facing. A wrong map
here costs the whole document.
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.
- 11d ago First seen · 331 lines · 107 tokens per session scan A d0a0023e5e28
manual is a skill published in the GitHub repository dougstanford/living-manual (3 stars, last pushed 29d ago), licensed MIT. It adds 107 tokens to every session and 3,747 once invoked, about $0.0005 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
plan
Research the codebase and create an implementation plan following Propose/Justify/Recommend. Use this before any feature, fix, or refactor.
multi-perspective-review
Multi-perspective collaborative review of plans or documents. Ten expert viewpoints deliberate in 3 rounds to reach consensus.
review
Run a full code review on current changes or specified files. Runs ruff lint, review-code agent, and security scan in sequence.
plan-task
Structured task planning using Work files. Use for any new feature, bug fix, or project that needs a task breakdown before implementation.
brainstorming
Design and spec before any planning or code. MUST USE before new features, creative work, or any implementation. Explores requirements, proposes approaches, gets design approval, then chains to plan-task.
journey-simulation
Use when caller wants to observe how a stranger encounters a flow, artifact, or sandbox — triggers like "simulate a user journey", "test our onboarding / checkout / signup", "will my ICP convert", "how does a cold reader experience this README", "first-time user test", "cognitive walkthrough", or any request to…