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 rules/jasonchen0604/codebase-to-portfolio/generate-tech-profile-jsongit clone --depth 1 https://github.com/jasonChen0604/codebase-to-portfolioWrote 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/rules/jasonchen0604/codebase-to-portfolio/generate-tech-profile-json)<a href="https://agentmods.dev/rules/jasonchen0604/codebase-to-portfolio/generate-tech-profile-json"><img src="https://agentmods.dev/badge/rules/jasonchen0604/codebase-to-portfolio/generate-tech-profile-json.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 | $0.00081 | $0.04409 |
| Opus 5 | $0.00041 | $0.02204 |
| Sonnet 5 | $0.00016 | $0.00882 |
| Haiku 4.5 | $0.00008 | $0.00441 |
Grade A, and why
generate-tech-profile-json 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 4d 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 — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Tech Profile JSON Skill
Goal
Read all project docs (doc_filename) with the latest skill_version, extract structured frontmatter data, then generate a tech-profile/ split-file directory (schema version 2.0).
Output layout:
tech-profile/
├── meta.json # meta + profile + linkedin + id_map
├── domains-<lang>.json # one per configured language
├── tag-index-<lang>.json # one per configured language
├── product-groups-<lang>.json # one per configured language
└── projects/
├── <hash>.<lang>.json # one file per project, per configured language
Why split? Each file is 1–15KB. Incremental runs only rewrite changed project files + rebuild the index files. Token cost scales with changed projects, not total project count.
Incremental update logic:
- Load existing
tech-profile/meta.json→ getid_mapandsource_version - Load all
tech-profile/projects/*.<primary_lang>.json→ build in-memory cache - For each project: compute hash, compare cached
skill_version- Unchanged → skip (reuse cached file, zero token cost)
- New or changed → read the doc file, write
<hash>.<lang>.jsonfor each configured language
- Always rebuild index files (domains, tag-index, product-groups) from all project files
- Write
meta.jsonwith updated totals
On first run (no existing tech-profile/), process all projects.
Step 0: Read config
Read profile.config.json from the current working directory. If missing, tell the user to copy examples/profile.config.example.json to profile.config.json and fill it in, then stop.
profile.name,profile.email,profile.title,profile.years_of_experience— used directly in theprofileJSON block (ifyears_of_experienceis absent, derive from the oldest project's last commit)doc_filename(defaultCLAUDE.md)languages(default["en"])timezone(default+00:00)privacy_blocklist(default[])custom_domains(default{}) — merged into the built-in domain table in Step 4
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.
- 4d ago First seen · 352 lines · 81 tokens per session scan A 8fbc91788e28
generate-tech-profile-json is a cursor rule published in the GitHub repository jasonChen0604/codebase-to-portfolio (2 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 4,409 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.
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