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 Montimage/skills --skill docs-generatorgit clone --depth 1 https://github.com/Montimage/skillsWrote 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/montimage/skills/docs-generator)<a href="https://agentmods.dev/skills/montimage/skills/docs-generator"><img src="https://agentmods.dev/badge/skills/montimage/skills/docs-generator/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/montimage/skills/docs-generator"><img src="https://agentmods.dev/badge/skills/montimage/skills/docs-generator.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 | $0.00035 | $0.01544 |
| Opus 5.5 | $0.00014 | $0.00618 |
| Sonnet 5.5 | $0.00007 | $0.00309 |
| Haiku 4.5 | $0.00003 | $0.00154 |
Grade A, and why
docs-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 23d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Generator
Restructure project documentation for clarity and accessibility.
When to Use
Use this skill when the user requests a clearer README, organized project docs, API references, architecture diagrams, or contributor guidance. Select only the documentation files relevant to the detected project type.
Prerequisites
- Work in a git repository with a configured
originremote and a clean or safely stashed working tree. - Identify the project's entry point, package manifest, test command, and existing documentation before drafting.
- Have write access to the target documentation paths; do not assume generated docs may replace source-authored content.
Repo Sync Before Edits (mandatory)
Before making any changes, sync with the remote to avoid conflicts:
branch="$(git rev-parse --abbrev-ref HEAD)"
git fetch origin
git pull --rebase origin "$branch"
If the working tree is dirty, stash first, sync, then pop. If origin is missing or conflicts occur, stop and ask the user before continuing.
Workflow
0. Create Feature Branch
Before making any changes:
- Check the current branch - if already on a feature branch for this task, skip
- Check the repo for branch naming conventions (e.g.,
feat/,feature/, etc.) - Create and switch to a new branch following the repo's convention, or fallback to:
feat/docs-generator
1. Analyze Project
Scan the project to understand its shape.
Use sub-agents for parallel discovery. Launch multiple Agent tool calls concurrently to keep the main context clean:
- Agent 1 — Stack detection: Scan for
package.json,pyproject.toml,Cargo.toml,go.mod,pom.xml, and identify the project type (library, API, web app, CLI, microservices), architecture (monorepo, multi-package, single module), and primary language(s). Return a structured summary. - Agent 2 — Existing docs inventory: List all existing documentation files (README.md, docs/, CONTRIBUTING.md, CHANGELOG.md, etc.) and summarize their current state — present, missing, or outdated. Return a checklist.
- Agent 3 — User personas & project purpose: Read the main entry point, existing README, and any project description fields to determine the project's purpose, key features, and target user personas (end users, developers, operators). Return a short summary.
What ships with it
2 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.
- 23d ago Changed · +40 lines · -90 tokens per session d065782f4e22
- 1mo ago First seen · 111 lines · 125 tokens per session scan A b0b95cfd866d
docs-generator is a skill published in the GitHub repository Montimage/skills (9 stars, last pushed 24d ago), licensed Apache-2.0. It adds 35 tokens to every session and 1,544 once invoked, about $0.0001 per session on Opus 5.5. 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
claude-md-improver
Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for generating K8s YAML manifests (use gke-manifest-generation) or disaster recovery…
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (auditcluster.sh), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (gVisor), enforcing Pod…
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and…
glance-canonical-layouts
Use this skill to create home screen widgets using Jetpack Glance Canonical Layouts from the Android Platform Samples project, or when asked to implement standard widget layout patterns (including Check List, Image Grid, Snap Scrolling, and Standard Toolbar).