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 etoyama/insight-blueprint --skill analysis-revisiongit clone --depth 1 https://github.com/etoyama/insight-blueprintWrote 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/etoyama/insight-blueprint/analysis-revision)<a href="https://agentmods.dev/skills/etoyama/insight-blueprint/analysis-revision"><img src="https://agentmods.dev/badge/skills/etoyama/insight-blueprint/analysis-revision/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/etoyama/insight-blueprint/analysis-revision"><img src="https://agentmods.dev/badge/skills/etoyama/insight-blueprint/analysis-revision.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 | $0.00068 | $0.02147 |
| Opus 5 | $0.00034 | $0.01073 |
| Sonnet 5 | $0.00014 | $0.00429 |
| Haiku 4.5 | $0.00007 | $0.00215 |
Grade A, and why
analysis-revision 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 9d 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/analysis-revision — Structured Review Revision
Guides the user through a structured revision workflow for an analysis design that has received review comments. Reads review feedback via MCP, creates a persistent tracking file for per-comment progress, and helps address each comment through interactive dialogue.
When to Use
- Design status is
revision_requestedand review comments need to be addressed - Resuming a previously interrupted revision session
- Systematically working through all reviewer feedback before re-submitting
When NOT to Use
- Creating a new design from scratch (-> /analysis-design)
- Recording reasoning during active analysis (-> /analysis-journal)
- Structured reflection and conclusion (-> /analysis-reflection)
- Design is not in
revision_requestedstatus
Workflow
Phase 1: Situation Assessment
-
If
$ARGUMENTScontains a design ID (e.g., "FP-H01"), use it directly. Otherwise, calllist_analysis_designs(status="revision_requested")and ask the user to select. -
get_analysis_design(design_id)-- load the design. -
Status check: If
status != "revision_requested", display an error and exit:このデザイン ({design_id}) は revision_requested 状態ではない (現在: {status})。 レビューで修正依頼が出た後にこのスキルを使おう。 -
get_review_comments(design_id)-- get all review batches. -
Batch selection (important -- do NOT just pick the newest batch overall):
- Filter the returned batches to only those where
status_after == "revision_requested" - From the filtered set, pick the one with the newest
created_at - This is the target batch for this revision session
- Filter the returned batches to only those where
-
If no qualifying batch found (all batches have
status_after != "revision_requested"):revision_requested に対応するレビューバッチが見つからない。 レビューが WebUI 経由で提出されているか確認しよう。Exit.
-
Display situation summary:
-- Revision: {design_id} -- Title: {title} Status: {status} Target batch: {batch.id} ({batch.created_at}) Reviewer: {batch.reviewer} Comments: {len(batch.comments)} items
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.
- 9d ago First seen · 227 lines · 68 tokens per session scan A 6af08d00ccab
analysis-revision is a skill published in the GitHub repository etoyama/insight-blueprint (0 stars, last pushed 17d ago), licensed MIT. It adds 68 tokens to every session and 2,147 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
rival-search-mcp
Deterministic deep research via RivalSearchMCP. 9 tools: 5-engine web search (DuckDuckGo/Bing/Yahoo/Mojeek/Wikipedia), 9-platform social search (Reddit/HN/StackOverflow/Dev.to/Medium/ProductHunt/Bluesky/Lobste.rs/Lemmy), 5-source news (Google/Bing/Guardian/GDELT/DDG), 5 academic DBs…
safe-email-operations
Use email through the bundled mcp-email-server MCP server, diagnose bounded non-secret state, and hand account or credential setup to a user-operated CLI or authenticated local UI.
naver-search-mcp
Use for Korean web search, Naver News, Blog, Cafe, Image, Knowledge iN, Encyclopedia, Local search, and Naver DataLab search-trend and shopping-insight analysis through the published npm MCP server.
mcp-musescore
Use the ghchen99/mcp-musescore MCP server to inspect, navigate, compose, and edit an open MuseScore score through its QML WebSocket plugin.
ocr-expert
You are connected to OCR-MCP, a FastMCP 3.4+ server with 14 OCR backends. This skill teaches you how to use it effectively.
skills
Generate a complete SVG file from a natural language description using SEP-1577 multi-step sampling.