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Use cases: testing, devops, productivity, agent-building
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Files it touches
~/.claude/skills/eval-add
What's inside
- Skill name
eval-add- Description
- Stage 4 (Test) continuous evals. Turn a production incident, a fixed bug, or a real recent task into a permanent eval case under evals/cases/ so the agent configuration (CLAUDE.md, skills, hooks, REVIEW.md) is regression-tested in CI. Use on /sdlc:eval-add or when asked to add an eval / regression case for the agent.
- License
- MIT
- Instructions
- 43 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# /sdlc:eval-add — every incident becomes an eval
Read `sdlc-loop`. Evals are the AI-native equivalent of stage-gate QA: a suite that runs whenever the agent's
configuration changes (CLAUDE.md, `.claude/**`, REVIEW.md, sdlc.config.json) and nightly.
## Build the case
1. Identify the source: an incident (`sdlc/incidents/<id>/intent.md` + the fixing PR), a PR, or a real task
from recent work (`--from-task`). Read what the agent should have done differently.
2. Write `evals/cases/<kebab-name>.json`:
```json
{
"name": "status-endpoint-403-for-other-customer",
"source": "sdlc/incidents/2026-07-03-status-leak",
"prompt": "Add GET /claims/{id}/status behind existing auth per sdlc/changes/<id>/spec.md.",
"setup": ["git checkout -q <base sha or fixture branch>"],
"allowed_tools": "Read,Edit,Write,Grep,Glob,Bash(make test),Bash(make lint)",
"max_turns": 40,
"checks": [
{ "type": "command", "run": "make test", "expect_exit": 0 },
{ "type": "command", "run": "make lint", "expect_exit": 0 },
{ "type": "file_contains","path": "claims-api/routes/status.py", "pattern": "require_auth" },
{ "type": "no_changes", "globs": ["tests/**", "src/gen/**"] },
{ "type": "output_contains", "pattern": "make test" }
]
}
```
Check types supported by `evals/check.sh`: `command`, `file_contains`, `file_not_contains`, `no_changes`,
`output_contains`, `output_not_contains`.
3. The prompt must be realistic (what a person would actually type), and the checks must define "acceptable"
deterministically: tests pass, lint clean, behaviour unchanged, policy followed.
4. Run it locally once: `evals/run.sh evals/cases/<name>.json`. It must pass with the current configuration
(it is a regression test, not a wish).
5. Commit on a branch, PR titled `eval: <name>`, description links the incident/PR. The team that owned the
incident owns the eval.
## Keep the suite alive
- As models improve, cases stop discriminating. Mark such cases `"retired": true` with a reason instead of
deleting them; `run.sh` skips retired cases.
- Aim for 20–50 live cases drawn from real tasks. Report the current count and pass rate after adding.From bibutikoley/ai-sdlc-claude, MIT.
More from bibutikoley/ai-sdlc-claude
- 0.564score
tracker-sync
bibutikoley
Keep the legacy tracker (Jira, YouTrack, GitLab issues, GitHub issues) and the Markdown artifacts linked according to sdlc.config.json sourceOfTruth (repo |…
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
security-policy
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The organisation's security policy as constraints on specs, plans, code and reviews.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
ux-standards
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Interaction, accessibility and content-structure standards for anything users touch.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
release
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Stage 5 (Deploy) release of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
review
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Stage 5 (Deploy) AI review of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
setup
bibutikoley
Install the AI-native SDLC loop into a product repository.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
spec
bibutikoley
Stage 2 (Design) of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
incident
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Stage 6 (Maintain) of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
intent
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Stage 1 (Plan) of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
metrics
bibutikoley
Compute and explain the AI-native SDLC's leading and lagging indicators from Git history, PR metadata and CI (intent time-to-commit, intent→spec, spec→plan…
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
plan
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Stage 3 (Build) entry of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
brand-guidelines
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The organisation's brand and content standards applied to specs and UI work.
SkillBFreshness: B★ 3Claude Code +9
Signals
- Stars
- 3
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 5, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/bibutikoley/ai-sdlc-claude
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from bibutikoley
- 0.564score
brand-guidelines
bibutikoley
The organisation's brand and content standards applied to specs and UI work.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
incident
bibutikoley
Stage 6 (Maintain) of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
intent
bibutikoley
Stage 1 (Plan) of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
metrics
bibutikoley
Compute and explain the AI-native SDLC's leading and lagging indicators from Git history, PR metadata and CI (intent time-to-commit, intent→spec, spec→plan…
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
plan
bibutikoley
Stage 3 (Build) entry of the AI-native SDLC.
SkillBFreshness: B★ 3Claude Code +9 - 0.564score
compliance-policy
bibutikoley
Regulatory and change-management obligations as constraints on specs, plans, releases and reviews.
SkillBFreshness: B★ 3Claude Code +9
Cite this page
eval-add skill. Agent Mart. https://agentmart.dev/skills/bibutikoley-eval-add (last updated 2026-10-24)