Borrowing it
Nothing to install: this file belongs to rigortype/rigor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/rigortype/rigor/master/.claude/skills/rigor-regression-sweep/SKILL.mdgit clone --depth 1 https://github.com/rigortype/rigorWrote 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/rigortype/rigor/rigor-regression-sweep)<a href="https://agentmods.dev/skills/rigortype/rigor/rigor-regression-sweep"><img src="https://agentmods.dev/badge/skills/rigortype/rigor/rigor-regression-sweep/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/rigortype/rigor/rigor-regression-sweep"><img src="https://agentmods.dev/badge/skills/rigortype/rigor/rigor-regression-sweep.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00050 | $0.03015 |
| Opus 5.5 | $0.00020 | $0.01206 |
| Sonnet 5.5 | $0.00010 | $0.00603 |
| Haiku 4.5 | $0.00005 | $0.00301 |
Grade A, and why
rigor-regression-sweep 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 11d 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 — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rigor Regression Sweep
A contributor workflow for measuring how Rigor's diagnostics
behave over a real project's development flow. Pick an OSS Ruby
project, baseline it at one version, then run rigor check against
every later tag with that baseline + config frozen. The
per-tag surfaced diagnostic count is the "error increase" a team
adopting Rigor in acknowledge mode would have seen.
It validates two things at once: the baseline mechanism
(ADR-22) and the realism of the rigor-project-init acknowledge-
mode environment — and grows an empirical corpus under
docs/notes/.
First worked run: docs/notes/20260521-mastodon-v4.5-regression-sweep.md
(Mastodon, 16 tags v4.5.0-beta.1 → v4.5.10).
Phase 0 — When to use
Trigger when asked to "sweep Rigor across versions of X", "check how the error count grows over a release line", "validate the baseline against real churn", or to add a project to the regression corpus.
Do NOT use for: a single-version check of one project (just run
rigor check); authoring a plugin (rigor-plugin-author); the
22-library single-snapshot survey style of
docs/notes/20260519-oss-library-survey.md
(that is breadth; this is depth-over-time for one project).
Phase 1 — Pick the target and the tag range
Choose a real OSS Ruby project with git tags.
The sampling decision is the single most important one — and it governs what the sweep can prove.
Released tags are a post-spec-gate population. A mature project's CI catches obvious errors before merge, and genuine bugs are fixed before a tag is cut. So a sweep over released tags — whether a patch series or a feature-spanning minor/major range — measures:
- baseline stability — does ordinary maintenance churn produce false regressions? (a real, valuable question), and
- standing diagnostics — does newly-added released code carry diagnostics the baseline did not already cover?
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 269 lines · 50 tokens per session scan A a1befcce383c
rigor-regression-sweep is a skill published in the GitHub repository rigortype/rigor (107 stars, last pushed today), licensed MPL-2.0. It adds 50 tokens to every session and 3,015 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 2026-10-26.
rigor-regression-sweep compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| rigor-regression-sweeprigortype/rigor | Skill | 107 | today | MPL-2.0 | A | 50 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |