Borrowing it
Nothing to install: this file belongs to markmhendrickson/foundation. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/markmhendrickson/foundation/main/.cursor/skills/analyze/SKILL.mdgit clone --depth 1 https://github.com/markmhendrickson/foundationWrote 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/markmhendrickson/foundation/analyze)<a href="https://agentmods.dev/skills/markmhendrickson/foundation/analyze"><img src="https://agentmods.dev/badge/skills/markmhendrickson/foundation/analyze/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/markmhendrickson/foundation/analyze"><img src="https://agentmods.dev/badge/skills/markmhendrickson/foundation/analyze.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 | $0.00013 | $0.04776 |
| Opus 5.5 | $0.00005 | $0.01910 |
| Sonnet 5.5 | $0.00003 | $0.00955 |
| Haiku 4.5 | $0.00001 | $0.00478 |
Grade A, and why
analyze 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 1mo 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.
This is a copy
100% identical to analyze — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 567 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Project
Analyze any project (URL or term) from both competitive and partnership perspectives relative to all repositories (comparative analysis across your repos). Load repo list from the truth layer (per neotoma_parquet_migration_rules.mdc).
Command
analyze <url_or_term>
Input
Accepts:
- Full URL (e.g.,
analyze https://memorae.ai) - Domain name (e.g.,
analyze memorae.ai) - Search term (e.g.,
analyze "memory layer productivity")
Examples:
analyze memorae.aianalyze https://memorae.aianalyze "memory layer productivity tool"
Workflow Overview
This command performs systematic analysis following the framework defined in foundation/strategy/project_assessment_framework.md. The analysis type depends on the resource:
For Products/Projects:
- Load all repos from truth layer (per
neotoma_parquet_migration_rules.mdc) - Discover repo context for current repo and all repos in the loaded list
- Research target project via web scraper MCP (if ChatGPT/Twitter URL) or browser tools
- Generate competitive analysis using standardized template (compare target vs. each repo)
- Generate partnership analysis using standardized template (compare target vs. each repo)
- Save both analyses to private docs submodule
- Present summary to user (including comparative summary across repos)
For Content/Thought Leadership (Articles, Research, etc.):
- Load all repos from truth layer (per
neotoma_parquet_migration_rules.mdc) - Discover repo context for current repo and all repos in the loaded list
- Research target resource via web scraper MCP (if ChatGPT/Twitter URL) or browser tools
- Generate holistic relevance analysis using relevance template (applicable to each repo)
- Save analysis to private docs submodule
- Present summary to user (including relevance to each repo where applicable)
Output:
- Products/Projects:
- Competitive analysis:
docs/private/competitive/[target_name]_competitive_analysis.md - Partnership analysis:
docs/private/partnerships/[target_name]_partnership_analysis.md
- Competitive analysis:
- Content/Thought Leadership:
- Relevance analysis:
docs/private/insights/[target_name]_relevance_analysis.md
- Relevance analysis:
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.
- 1mo ago First seen · 567 lines · 13 tokens per session scan A fa5584ff3a2f
analyze is a skill published in the GitHub repository markmhendrickson/foundation (2 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 4,776 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to analyze, differing in 11 lines, and is treated as a copy.
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