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 FarzamMohammadi/the-engineer --skill investigate-projectgit clone --depth 1 https://github.com/FarzamMohammadi/the-engineerWrote 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/farzammohammadi/the-engineer/investigate-project)<a href="https://agentmods.dev/skills/farzammohammadi/the-engineer/investigate-project"><img src="https://agentmods.dev/badge/skills/farzammohammadi/the-engineer/investigate-project/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/farzammohammadi/the-engineer/investigate-project"><img src="https://agentmods.dev/badge/skills/farzammohammadi/the-engineer/investigate-project.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 | $0.00089 | $0.01592 |
| Opus 5 | $0.00044 | $0.00796 |
| Sonnet 5 | $0.00018 | $0.00318 |
| Haiku 4.5 | $0.00009 | $0.00159 |
Grade A, and why
investigate-project 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 12d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigate Project
Perform a thorough, multi-perspective investigation of an external open-source project and produce a comparative analysis document against The Engineer. The output matches the established format in docs/archived/implementation-docs/considered-projects/.
The goal is an honest, thorough analysis — not marketing. We want to understand what the project actually is (not what it claims to be), what it does well, what The Engineer does better, and what patterns are worth adopting. The document should be useful months later as a reference for architectural decisions.
Step 1: Understand the Format
Read 1-2 existing analyses from docs/archived/implementation-docs/considered-projects/ to internalize the established structure and tone. These are the gold standard — match their depth, honesty, and table-driven comparison style.
The standard structure is:
- What [Project] Is — honest description of what's actually built (not what the README claims)
- Direct Comparison — table-driven comparison across all relevant dimensions
- Architectural Analysis — what they do well, what The Engineer does better
- Patterns Worth Studying/Adopting — concrete ideas that could improve The Engineer
- Where We Stand — honest assessment with summary tables
Step 2: Launch Parallel Research
Launch 3 Explore sub-agents simultaneously, each with a distinct research focus. Every agent should use WebFetch to read actual file contents from the repository — not just README summaries.
Agent 1: Broad Overview + Technical Architecture
Research focus:
- What is this project? What problem does it solve?
- What's actually built vs. what's just documentation/prompts?
- Read the actual source code — entry points, core modules, key classes
- Tech stack, dependencies, package.json/requirements.txt
- How mature is it? (stars, contributors, release history, recent activity)
- Testing approach — read actual test files, understand coverage and quality
- What's the deployment model? Library, CLI, daemon, service?
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.
- 12d ago First seen · 142 lines · 89 tokens per session scan A 29e052c30fd3
investigate-project is a skill published in the GitHub repository FarzamMohammadi/the-engineer (12 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 1,592 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 2026-08-30.
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