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 agentmods add skills/etoyama/insight-blueprint/analysis-reflectionnpx skills add etoyama/insight-blueprint --skill analysis-reflectiongit 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-reflection)<a href="https://agentmods.dev/skills/etoyama/insight-blueprint/analysis-reflection"><img src="https://agentmods.dev/badge/skills/etoyama/insight-blueprint/analysis-reflection.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 | $0.00079 | $0.01443 |
| Opus 5 | $0.00039 | $0.00722 |
| Sonnet 5 | $0.00016 | $0.00289 |
| Haiku 4.5 | $0.00008 | $0.00144 |
Grade A, and why
analysis-reflection 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 5d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/analysis-reflection — Structured Analysis Reflection
Guides the user through a structured reflection on their analysis, using the Insight Journal as source material. Helps reach a conclusion, identify remaining gaps, or decide to branch.
When to Use
- Enough evidence has been gathered and it's time to reflect
- Want to assess open questions and decide next steps
- Ready to conclude (transition to supported/rejected/inconclusive)
When NOT to Use
- Still actively investigating (→ /analysis-journal)
- Creating a new design (→ /analysis-design)
- Registering data sources or knowledge (→ /catalog-register)
Workflow
Step 1: Load Design + Journal
get_analysis_design(design_id)— load design- Read
.insight/designs/{design_id}_journal.yamlusing Read tool — load journal - If no journal exists: "ジャーナルがない。まず /analysis-journal {id} で推論過程を記録してから振り返ろう" → exit
Step 2: Present Analysis Summary
Show structured overview:
── Reflection: {design_id} ──
Title: {title}
Hypothesis: {hypothesis_statement}
Intent: {analysis_intent}
Status: {status}
── Journal Overview ──
Total events: {count}
Phase: {inferred_phase} (see /analysis-journal Phase Inference rules)
Timeline: {first_event.created_at} → {last_event.created_at}
── Evidence ──
Supporting: {count} items
- {content} ({created_at})
Contradicting: {count} items
- {content} ({created_at})
── Decisions Made ──
- {method} ({package}) — {reason}
── Open Questions ──
- {question_content} ({event_id})
── Branches ──
- {child_design_id}: {child_title} ({child_status})
To find branches, use:
children = [d for d in list_analysis_designs(theme_id=design.theme_id) if d.parent_id == design_id]
Step 3: Guided Reflection (3 Questions)
Ask in sequence. Record each answer as a reflect event in the journal.
Q1: Evidence Assessment "証拠を総合すると、仮説「{hypothesis_statement}」についてどう言える?"
- Supporting evidence dominant → supported direction
- Contradicting evidence dominant → rejected direction
- Inconclusive → inconclusive direction or more investigation
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.
- 5d ago First seen · 156 lines · 79 tokens per session scan A f9369b23bd82
analysis-reflection is a skill published in the GitHub repository etoyama/insight-blueprint (0 stars, last pushed 13d ago), licensed MIT. It adds 79 tokens to every session and 1,443 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 2026-08-31.
Other skills, from other repositories
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.
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…
mcp-server-architect
Comprehensive MCP server development guide covering FastMCP 2.14.3 features, Anthropic standards, ecosystem integration, and production deployment across all agentic IDEs.
mcp-musescore
Use the ghchen99/mcp-musescore MCP server to inspect, navigate, compose, and edit an open MuseScore score through its QML WebSocket plugin.
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.
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.