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 yohey-w/codd-dev --skill codd-scangit clone --depth 1 https://github.com/yohey-w/codd-devWrote 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/yohey-w/codd-dev/codd-scan)<a href="https://agentmods.dev/skills/yohey-w/codd-dev/codd-scan"><img src="https://agentmods.dev/badge/skills/yohey-w/codd-dev/codd-scan/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/yohey-w/codd-dev/codd-scan"><img src="https://agentmods.dev/badge/skills/yohey-w/codd-dev/codd-scan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.01248 |
| Opus 5.5 | $0.00023 | $0.00499 |
| Sonnet 5.5 | $0.00012 | $0.00250 |
| Haiku 4.5 | $0.00006 | $0.00125 |
Grade A, and why
codd-scan 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.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CoDD Scan
Refresh the CoDD dependency graph from document frontmatter and source code so later commands (codd validate, codd impact, codd generate, codd verify) operate on current project state. Use this after requirements, design docs, implementation, or tests change.
When to Use
- After editing Markdown files with CoDD frontmatter
- After adding or changing source files that affect dependencies
- Before
codd impactwhen you need a fresh graph - When scan counts look stale or unexpectedly low
Preconditions
- Resolve the target project root first. Prefer an absolute path when the working directory is ambiguous.
- Check whether
codd/codd.yamlexists under that path. - If
codd/codd.yamlis missing, initialize CoDD before scanning:
codd init --project-name "<project-name>" --language "<language>" --dest <path>
- If
coddis not onPATH, use one of these:pip install codd-dev.venv/bin/codd scan --path <path>
Command
Run the scan from anywhere by passing the project root explicitly:
codd scan --path <path>
If you are already at the project root, codd scan --path . is sufficient.
What the Scan Does
- Reads
codd/codd.yaml - Rebuilds auto-generated graph data from project documents and source code
- Preserves human-authored evidence
- Prints a short summary of frontmatter coverage and graph size
How to Interpret the Result
Typical output includes:
Scan complete:
Documents with frontmatter: <count>
Graph: <nodes> nodes, <edges> edges
Evidence: <total> total (...)
Documents with frontmatter: how many Markdown documents in configureddoc_dirswere successfully read as CoDD documents. If this is lower than expected, inspect missing frontmatter or wrongdoc_dirs.nodes: the number of tracked artifacts in the graph. In document-centric projects this is usually close to the total number of requirements/design/test artifacts being tracked.edges: the total number of declared or inferred dependency relationships between those artifacts.orphan nodes: artifacts that have no surviving dependency relationship. They are often a sign of missingdepends_on, stale docs, or a document that should be deleted. Some top-level requirements may be intentional exceptions, but unexplained orphans should always be reviewed.WARNING:lines: scan found suspicious input such as missing frontmatter or design docs with empty dependencies. Treat warnings as a prompt to runcodd validate.SCAN_ERROR(if surfaced by your wrapper, report script, or higher-level UI): frontmatter could not be parsed or read cleanly. Treat it as a validation problem and inspect the document withcodd validate --path <path>.
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 · 124 lines · 58 tokens per session scan A 937b32390ff1
codd-scan is a skill published in the GitHub repository yohey-w/codd-dev (115 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 1,248 once invoked, about $0.0002 per session on Opus 5.5. 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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