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/yohey-w/codd-dev/codd-impactnpx skills add yohey-w/codd-dev --skill codd-impactgit clone --depth 1 https://github.com/yohey-w/codd-devWhat 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 | $0.00056 | $0.01319 |
| Opus 5 | $0.00028 | $0.00660 |
| Sonnet 5 | $0.00011 | $0.00264 |
| Haiku 4.5 | $0.00006 | $0.00132 |
Grade A, and why
codd-impact scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CoDD Impact Analysis
Use this skill after a requirements, design, code, or test change to determine what CoDD artifacts must be updated next. The goal is not only to read the impact report, but to decide whether the AI should update design documents immediately, ask a human for approval, or only report informational findings. Treat the impact report as an action queue for keeping requirements, design, implementation, and tests coherent.
Primary Command
Run impact analysis from the project root:
codd impact --path .
By default, this detects uncommitted changes (compares working tree to HEAD). No need to commit first.
If you need a report file:
codd impact --path . --output "codd/reports/impact_$(date +%Y%m%d_%H%M%S).md"
If you need to compare against a specific commit instead of uncommitted changes:
codd impact --diff <commit-hash> --path .
Preflight
- Confirm you are at the project root and
codd/codd.yamlexists. - Confirm
codd/scan/directory exists (contains nodes.jsonl and edges.jsonl). - If
codd/scan/is missing or empty, run:
codd scan --path .
- Run
codd impact --path .. - Read the report in this order:
- Convention Alerts
- Green Band
- Amber Band
- Gray Band
How To Act On Each Band
Convention Alerts
Convention Alerts have higher priority than Green, Amber, or Gray items. They mean an implicit rule may have been violated.
When a Convention Alert appears:
- Open
codd/annotations/conventions.yaml. - Find the rule that matches the reported target and reason.
- Identify which invariant is being protected and which changed artifact triggered it.
- Update the affected design docs, tests, or governance docs so the invariant is either preserved or explicitly re-decided.
- If the business rule itself changed, do not silently override it. Ask the human to confirm the convention change before editing
conventions.yaml.
Green Band
Green Band means the impact is high-confidence and the AI may update affected design documents autonomously.
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.
- 3d ago First seen · 167 lines · 56 tokens per session scan A cdad3e21537e
codd-impact is a skill published in the GitHub repository yohey-w/codd-dev (114 stars, last pushed 22d ago), licensed MIT. It adds 56 tokens to every session and 1,319 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…