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.
git clone --depth 1 https://github.com/thangnguyenworkspace/company-research-pipelineWrote 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/commands/thangnguyenworkspace/company-research-pipeline/repo-recon)<a href="https://agentmods.dev/commands/thangnguyenworkspace/company-research-pipeline/repo-recon"><img src="https://agentmods.dev/badge/commands/thangnguyenworkspace/company-research-pipeline/repo-recon/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/commands/thangnguyenworkspace/company-research-pipeline/repo-recon"><img src="https://agentmods.dev/badge/commands/thangnguyenworkspace/company-research-pipeline/repo-recon.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 | $0.00015 | $0.00703 |
| Opus 5 | $0.00008 | $0.00351 |
| Sonnet 5 | $0.00003 | $0.00141 |
| Haiku 4.5 | $0.00002 | $0.00070 |
Grade A, and why
repo-recon scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Use free direct fetches (`curl`) against the GitHub REST API; no search product needed: How it starts
The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repo Recon
Explore the GitHub target in $ARGUMENTS to establish what a company's public code actually shows: what is real, what is active, what is a shell. If no target was given, ask.
The engineering surface is one of the highest-signal, lowest-cost verification sources in company research: it is primary, it is dated, and it cannot be retro-edited the way a marketing page can.
Step 1: Scan (breadth before depth)
Use free direct fetches (curl) against the GitHub REST API; no search product needed:
- Org level (when the target is an owner):
GET /orgs/{owner}/repos(or/users/{owner}/repos). Capture per repo: name, description, language, created/pushed dates, stars, forks, archived flag. - Repo level:
GET /repos/{owner}/{repo}for metadata, then the README viaraw.githubusercontent.com/{owner}/{repo}/{default_branch}/README.md, then the file tree via the contents or git-trees API. - Build the scan report: a repo inventory table plus, for the focal repo, the README summary and tree outline, ending with 3 to 6 drill candidates (the files or questions most worth a deep look).
Present the scan and pause: let the user pick drill targets before spending depth.
Step 2: Dive (rounds, on request)
Per drill round: fetch the chosen files (raw fetches; /exa-crawl for rendered pages like release notes or hosted docs), and answer the round's question concretely.
High-signal checks for company research, from practice:
- Activity reality: last-push dates across the org. One actively committed repo surrounded by frozen forks tells you where the real work is (usually a private monorepo).
- Fork depth: for a repo forked from an upstream,
GET /repos/{owner}/{repo}/compare/{upstream-default}...{default}shows ahead/behind counts. Check a rebase or integration branch too; a big behind-count on the default branch often just means upstream velocity, not dormancy. The ahead-commits are the company's actual contribution; read their themes. - Shipped vs marketed: does the "get started" repo linked from marketing actually contain code? Does the SDK's repository field resolve (a 404 means closed source behind a public npm package)?
- External traction: stars, forks, and who imports the packages. Registry download curves that spike on release dates and collapse between them indicate internal CI, not adoption.
- Cross-check the package registry directly (
registry.npmjs.org/{package}JSON): versions, publish cadence, maintainers. Live registry beats any cached search result.
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 · 37 lines · 15 tokens per session scan A 751d7e5f3102
repo-recon is a command published in the GitHub repository thangnguyenworkspace/company-research-pipeline (2 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 703 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
create-actor
Guided Apify Actor development with best practices and systematic workflow.
status
Show current research session state and progress.
resume
Resume a previous research session from progress file.
init
Manually initialize or reload research context for sigint.
augment
Deep-dive into a specific area of current research.
issues
Create GitHub issues from research findings as atomic deliverables.