New Module: ai-lifecycle — AI/ML project lifecycle agentic team - #17
New Module: ai-lifecycle — AI/ML project lifecycle agentic team#17avielbl wants to merge 3 commits into
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No actionable comments were generated in the recent review. 🎉 ℹ️ Recent review info⚙️ Run configurationConfiguration used: Organization UI Review profile: CHILL Plan: Team Run ID: 📒 Files selected for processing (1)
Included review availability: Your plan provides up to 1 included review per hour; 0 remain after this review. WalkthroughThe community registry entry for ChangesCommunity Module Registry Entry
Estimated code review effort: 1 (Trivial) | ~2 minutes Merge Risk: ⚪ Minimal · up to This PR adds and updates registry metadata for the ai-lifecycle module without introducing a concrete correctness, security, availability, or deployment risk; no actionable merge-blocking risk remains after normal checks and review. Poem
🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
Full details: Docstring CoverageExplanation No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check. Docstring coverage is scoped to functions touched by this diff. Analyzed 0 functions across 0 files. (1 skipped: 1 unsupported.) ✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 1
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@registry/community/ai-lifecycle.yaml`:
- Around line 22-27: This entry mixes unverified status with filled approval
metadata: update the fields so they are consistent—either set trust_tier to a
reviewed value (e.g., community-reviewed or bmad-certified) and replace reviewer
with the reviewer’s GitHub handle while keeping approved_tag, approved_sha, and
approved_date, or clear approved_tag, approved_sha, approved_date and set
reviewer to an empty string (or remove it) while leaving trust_tier: unverified;
adjust the trust_tier, reviewer, and approved_* fields accordingly to remove the
semantic contradiction.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: Organization UI
Review profile: CHILL
Plan: Pro
Run ID: 8a592410-0fe6-4884-866b-56d2bb63ad82
📒 Files selected for processing (1)
registry/community/ai-lifecycle.yaml
| version: "4.0.0" | ||
| approved_tag: v4.0.0 | ||
| approved_sha: 6c992499636c0a53b4f4ae6f30ab8cfbd17ea9cc | ||
| trust_tier: unverified | ||
| approved_date: "2026-05-04" | ||
| reviewer: pending |
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🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
set -euo pipefail
echo "== reviewer schema =="
rg -n "reviewer:" registry/registry-schema.yaml
echo "== trust_tier schema =="
rg -n "trust_tier:" registry/registry-schema.yaml
echo "== community module approval fields section =="
rg -n "approved_tag|approved_sha|approved_date" registry/registry-schema.yaml
echo "== dump this registry entry =="
python - <<'PY'
import sys, yaml, pathlib
p = pathlib.Path("registry/community/ai-lifecycle.yaml")
print(p)
print(p.read_text())
PY
echo "== optional: run any registry validation script if present =="
# Best-effort: detect a likely validator command
ls -la .
ls -la registry || true
ls -la .github || true
# If you have a script/Make target, run it here (adjust name if needed).Repository: bmad-code-org/bmad-plugins-marketplace
Length of output: 2932
🏁 Script executed:
cat -n registry/registry-schema.yamlRepository: bmad-code-org/bmad-plugins-marketplace
Length of output: 3512
🏁 Script executed:
ls -la .github/scripts/
fd -t f validator registryRepository: bmad-code-org/bmad-plugins-marketplace
Length of output: 260
Semantic contradiction: trust_tier: unverified with populated approved_* fields and reviewer: pending.
The registry schema comments (lines 80-84 of registry-schema.yaml) explicitly document that reviewer should be a "GitHub handle of reviewer" and that approved_tag, approved_sha, approved_date are required for community modules. However, this entry uses reviewer: pending (not a GitHub handle) and populates all approved_* fields while simultaneously setting trust_tier: unverified. This contradicts the documented intent that approval fields should only be populated for verified/reviewed entries.
Either set trust_tier to an appropriate value (e.g., community-reviewed or bmad-certified) if the module is approved, or leave the approved_* fields and reviewer empty/blanked and set trust_tier: unverified to indicate pending review. Do not mix unverified status with populated approval metadata.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@registry/community/ai-lifecycle.yaml` around lines 22 - 27, This entry mixes
unverified status with filled approval metadata: update the fields so they are
consistent—either set trust_tier to a reviewed value (e.g., community-reviewed
or bmad-certified) and replace reviewer with the reviewer’s GitHub handle while
keeping approved_tag, approved_sha, and approved_date, or clear approved_tag,
approved_sha, approved_date and set reviewer to an empty string (or remove it)
while leaving trust_tier: unverified; adjust the trust_tier, reviewer, and
approved_* fields accordingly to remove the semantic contradiction.
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The CodeRabbit finding is a false positive. The CONTRIBUTING.md submission template explicitly shows this exact pattern — |
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@avielbl thank you - team is reviewing! |
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@avielbl I spot checked a few things and there are missing file references that various skills are told to run - you will want to probably scan with claude or similar for references across skills that are referencing something that does not existing within the skill |
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Good catch — thanks. Scanned every
Pushed as avielbl/ai-lifecycle@1425015. Test suite (20 tests) still passes. Please re-pull when you get a chance and let me know if anything else looks off. |
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@bmadcode, have you had the chance to review my latest corrections per your comments? |
Hi, I've addressed the raised issues regarding file references. Thanks, |
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Hi @bmadcode , any updates on this PR? |
Pins the registry entry to tag v5.1.0 (sha 94f4b50). Since v4.0.0 the module adds: Stage 9 deployment, per-project memory bank, literature review stage, executed EDA notebooks, MCP-first internal-source integrations with air-gapped support, review-gate conventions, prompt flavors (standard/guided), and opencode/Copilot harness support. Description updated accordingly. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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@bmadcode The submission is now updated to v5.1.0 (tag pinned, SHA 94f4b50, branch synced with main). Since your May review, all flagged file references were fixed, and the module has since added Stage 9 deployment, a per-project memory bank, literature review, air-gapped/MCP integrations, and multi-harness support. The entry format follows the merged suno-band-manager pattern. Ready for re-review. |
2 participants
New Module Submission
Module: ai-lifecycle
Repository: https://github.com/avielbl/ai-lifecycle
Version: v4.0.0
Author: Aviel
License: MIT
What it does
A structured agentic team of 5 specialist agents that guide an AI/ML project from raw domain research through production inference:
Works across deep learning, gradient boosting (XGBoost/LightGBM), transformers, fine-tuning, and classical ML.
Checklist
bmad-manifest.jsonper agent,SKILL.mdfrontmatter,module.yaml)validate_skills.ymlon PRs).claude-plugin/marketplace.jsonv4.0.0(6c992499636c0a53b4f4ae6f30ab8cfbd17ea9cc)ai-and-machine-learning/mlopsSummary by CodeRabbit