lint-cdc
Skill10 starsChanged 53 days agoMITView on GitHub
Check RTL lint and clock-domain crossings with SpyGlass, evaluate violations and justified waivers, and close the current assessment.
In this repository13 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/CLAUDE.mdCLAUDE.md
- brainstormSkill
- design-flowSkill
- env-precheckSkill
- power-analysisSkill
- rtl-designSkill
- simulation-planSkill
- simulationSkill
- simulation-triageSkill
- specificationSkill
- synthesisSkill
- timing-analysisSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
Write under {workdir}; upstream inputs remain read-only.
- Very specific: line 29
Run make lint, make cdc, or make all from the prepared workdir.
- Very specific: line 46
Use --fail-reason for unjustified waivers or invalid/incomplete checks, even when counts are zero.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Lint and CDC
Assess the RTL against the task's lint and CDC requirements. Read dispatch.json, original intent,
requirements, RTL, constraint annotations and specification SGDC. Use carried evidence when its
implementation, setup and scope still apply; choose the checks the current task needs.
Write under {workdir}; upstream inputs remain read-only. The framework carries published setup
and reports into this directory, without the old verdict. Keep useful analysis in evidence/.
Prepare and check
<skill> is this skill's directory:
python3 <skill>/scripts/lintcdc/__main__.py bootstrap --workdir {workdir}Bootstrap installs missing setup without overwriting authored files and refreshes the file list
and generated SGDC. constraint-annotations.json
supplies synchronizer, reset, case-analysis and quasi-static declarations. Check inherited
scripts/local.sgdc and scripts/waiver.tcl against the current design. Correct invalid input
declarations at their source.
Run make lint, make cdc, or make all from the prepared workdir; all shares elaboration.
The entrypoint withdraws the selected check's old summaries before execution. Wait for completion,
read the reports and inspect both reported and waived violations. The reports include native
waiver details when messages were waived. Record the basis in -comment, with evidence references
where needed; assess it against the requirements, including whether limits apply before or after waivers.
Repair local setup errors and rerun the affected checks.
Judge and close
python3 <skill>/scripts/lintcdc/__main__.py finalize --workdir {workdir} \
[--requirements '[{"id":"R-1","met":true,"actual":"observed result","measured":"report and scope"}]'] \
[--fail-reason "unresolved cause"] [--fix-owner <rule>]Declare a judgment for every lint-cdc requirement using the reports and the actual waiver policy.
finalize reads lint-violations.json and cdc-violations.json; it does not judge waiver reasoning.
Use --fail-reason for unjustified waivers or invalid/incomplete checks, even when counts are zero. Name
the repair owner from the defect, including this stage for its own setup; do not infer ownership
from the path of an error. Attribution guidance describes the constraint sources to check.
Acceptance changes follow the user's actual authorization.
Finalize withdraws the previous result before judging. Exit 0 means a pass/fail result was written;
return STATUS: DONE. On a nonzero exit, resolve the cause or return STATUS: BLOCKED <cause>.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

