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/marcoemrich/agentic_coding_lab/build-overviewnpx skills add marcoemrich/agentic_coding_lab --skill build-overviewgit clone --depth 1 https://github.com/marcoemrich/agentic_coding_labWrote 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/marcoemrich/agentic_coding_lab/build-overview)<a href="https://agentmods.dev/skills/marcoemrich/agentic_coding_lab/build-overview"><img src="https://agentmods.dev/badge/skills/marcoemrich/agentic_coding_lab/build-overview.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 | $0.00036 | $0.06065 |
| Opus 5 | $0.00018 | $0.03033 |
| Sonnet 5 | $0.00007 | $0.01213 |
| Haiku 4.5 | $0.00004 | $0.00607 |
Grade A, and why
build-overview 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/build-overview — produce an experiment-overview snapshot
You produce a frozen, publishable research report from the current state of every findings.md under research/questions-claude/, research/questions-opencode/, research/questions-cross/, and research/workflow-dev/. The snapshot lands as a new file under research/reports/experiment-overview-YYYY-MM-DD.md.
Core principle
findings.md = living document, growing list of status-tagged findings.
Snapshot = frozen, table-heavy report at a point in time.
Both exist in parallel. The snapshot is not written from memory — it is filled in from an auto-generated skeleton.
Prerequisites
Required on $PATH for the Markdown snapshot (steps 1–5):
python3— runsexperiments/generate-snapshot-skeleton.py
Only needed when the user asks for a PDF (step 6):
pandoc— Markdown → HTML (any version ≥ 2.9 works)google-chrome(orchromium— adjust the binary name in step 6) — headless--print-to-pdfpdfinfo(Poppler utils) — optional, used for the PDF verification check
If a PDF was requested and one of its tools is missing, finish the Markdown snapshot and report which tool is unavailable so the user can install it — do not treat it as a failure of the whole run.
Lifecycle (6 steps)
Step 1 — generate the skeleton
Bash:
./experiments/generate-snapshot-skeleton.py
Before trusting the output, verify the script sees every RQ subtree. RQ_TREES in generate-snapshot-skeleton.py is a hardcoded list. When a new subtree appears under research/ (a new harness family, a new question class), the script silently omits it — no warning, no error, just a smaller snapshot. Cross-check the RQ count against the filesystem before proceeding:
# every dir with a README.md carrying an `id:` is an RQ
find research -mindepth 2 -maxdepth 2 -name README.md | xargs grep -l '^id:' | wc -l
./experiments/generate-snapshot-skeleton.py 2>&1 | grep 'RQs:'
If the two numbers disagree, add the missing subtree to RQ_TREES and regenerate — do not hand-patch the skeleton. (This bit in 2026-07: questions-pi/ and questions-cursor-cli/ were missing, which would have dropped 3 RQs and 140 runs from the report.)
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 · 225 lines · 36 tokens per session scan A 1e1b3765ca70
build-overview is a skill published in the GitHub repository marcoemrich/agentic_coding_lab (11 stars, last pushed 17d ago), licensed MIT. It adds 36 tokens to every session and 6,065 once invoked, about $0.0002 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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