P0 - Must Have

Backlog

Tracked features, ideas, and deferred work for grooming and future sessions.

P0 - Must Have

(Empty)

P1 - Should Have

Validate and verify orchestrator-discipline plugin hooks and processes

Source: Plugin creation session 2026-02-19 Added: 2026-02-19 Plan: plan/tasks-4-validate-orchestrator-discipline.md Description: The orchestrator-discipline plugin was created from session anti-pattern analysis. Its 2 hooks (pre-tool-orchestrator-read-warning.cjs, pre-tool-diagnostic-command-gate.cjs), rules/CLAUDE.md, skill, and investigation-escalation reference need end-to-end validation. Verify: hooks fire correctly on matching tool calls, hooks do NOT fire on legitimate orchestrator reads (BACKLOG.md, plan files, files being edited), rules load into session context, skill activates on trigger phrases, no personal/private data in any plugin file, plugin passes claude plugin validate. Suggested location: plugins/orchestrator-discipline/

SAM: Error Recovery / Rollback Procedures

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define explicit procedure when a task fails irrecoverably. How to undo artifact changes? How to restore artifact plane to consistent state after failure? Research first: How do GSD, BMAD-METHOD, AutoGPT, and traditional CI/CD handle rollback? What patterns exist for transactional artifact updates? Suggested location: stateless-software-engineering-framework.md (new Appendix or Part 6 addition)

SAM: Human Escalation Criteria

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define explicit triggers for escalating to human at each stage (not just Discovery). When should agents block and ask vs attempt repair vs fail? Research first: How do GSD deviation rules work? How does BMAD-METHOD handle human checkpoints? What escalation patterns exist in agent frameworks? Suggested location: stateless-software-engineering-framework.md (each Agent Specification section)

SAM: Timeout/Stall Detection

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define mechanism to detect when an agent is stuck or has stalled. Include timeout thresholds per stage, health check patterns, and recovery actions. Research first: How do orchestration frameworks (Temporal, Prefect, Airflow) handle task timeouts? What heartbeat patterns exist? How does Gas Town handle session recycling? Suggested location: stateless-software-engineering-framework.md (Orchestrator section 3.8)

SAM: Artifact Schema Validation

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define formal validation rules or JSON schemas for artifact formats. Currently only templates provided. Enable automated validation at stage boundaries. Research first: How do GSD artifacts (STATE.md, ROADMAP.md) enforce structure? What validation approaches exist in BMAD-METHOD? JSON Schema vs YAML validation vs custom parsers? Suggested location: sam-artifact-schemas/ (new directory with schema files)

SAM: Scope Creep Detection

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define mechanism to detect when execution diverges from plan. How does Forensic Review detect that the execution agent solved a different problem than planned? Research first: How does GSD plan-checker detect deviation? What diff/comparison techniques exist? How do code review tools detect scope creep in PRs? Suggested location: stateless-software-engineering-framework.md (section 3.6 Forensic Review)

Meta-Process Capture — Expert Panel Dataset Builder

Source: ARL expert panel process (sessions 2026-02-12 to 2026-02-13) Added: 2026-02-13 Description: Document the multi-agent expert panel methodology as a reusable system for building datasets that inform skills and systems. The process — assign framework experts to repositories, ask structured questions, cross-examine, synthesize, map to requirements, validate — produced high-quality sourced findings. Capture this as a repeatable pattern. Key elements to document:

• Expert assignment protocol (one agent per source repo, source-code-only evidence standard)
• Question group design (themed questions → cross-examination → synthesis)
• Cross-examination as adversarial validation (experts challenge each other's claims)
• Phased output (discussion → requirement mapping → synthesis → validation)
• Traceability chain (claim → expert citation → file:line evidence)
• Session continuity handling (state file enables cross-session resumption) Input artifacts: plugins/plugin-creator/skills/assessor/references/ARL/ARL-agent-instructions.md, qa-expert-panel.md Suggested location: New skill or methodology document — captures the meta-process, not the ARL content

SAM Extension — Integrate ARL General Theory

Source: ARL expert panel Phase 3 output Added: 2026-02-13 Description: Integrate the 7 universal principles from synthesis-general-theory.md into SAM methodology documents. These principles (structure over instruction, front-loading reduces gates, AI cannot self-evaluate, compression is architectural, iteration-aware state required, parallelism enables independent verification, failure paths need more compression) extend SAM's scope to cover autonomous refinement loops. Input artifacts: plugins/plugin-creator/skills/assessor/references/ARL/synthesis-general-theory.md Target files: stateless-agent-methodology.md, stateless-software-engineering-framework.md Dependencies: None — general theory is framework-agnostic Related backlog items: SAM gap items (error recovery, human escalation, scope creep detection) — the general theory findings inform several of these

ARL Skill Development

Source: ARL expert panel Phase 3 output Added: 2026-02-13 Description: Build the Autonomous Refinement Loop as a skill using synthesis-arl-applicable.md as its reference foundation. The ARL is a logical process (Assess → Plan → Implement → Review → Repeat) for autonomous skill refinement with R1-R10 requirement gates. Input artifacts: plugins/plugin-creator/skills/assessor/references/ARL/synthesis-arl-applicable.md, synthesis-general-theory.md Scope: Logical process design — what gates fire when, what each gate checks, success/failure criteria. NOT implementation artifacts (schemas, thresholds, pseudocode). Dependencies: Benefits from SAM extension being done first (ARL would be a SAM-based skill) Suggested location: New skill under plugins/plugin-creator/skills/ or standalone plugin

Extract claude-plugin-lint to standalone PyPI package

Source: Gap analysis - no existing Claude Code plugin linters exist Added: 2026-02-01 Description: Extract and enhance validate_frontmatter.py into a standalone open-source project. First dedicated linter for Claude Code plugin frontmatter (SKILL.md, agents/.md, commands/.md). Official claude plugin validate only checks plugin.json structure. Features to include:

• YAML frontmatter schema validation with Pydantic models
• Auto-fix capabilities (arrays → comma-separated, multiline → single-line)
• Token-based complexity metrics (tiktoken) instead of line counts
• Cross-reference validation (agent references non-existent skill)
• Marketplace readiness scoring
• Pre-commit hook integration
• CLI with --fix and --report modes Current source: plugins/plugin-creator/scripts/validate_frontmatter.py Suggested repo name: claude-plugin-lint or cc-plugin-validator

P2 - Could Have

kaizen: MCP consolidation analysis

Source: Design session 2026-02-20 Added: 2026-02-20 Description: The plugin currently runs two MCP servers (kaizen-duckdb via mcp-server-motherduck, kaizen-analysis via server.py) plus a standalone CLI script (sentiment-score.py). Investigate: (1) What does each MCP server provide that the other cannot? Can they be merged into a single server? (2) Why is sentiment-score.py a standalone script rather than an MCP tool inside server.py? What would be gained or lost by moving scoring into the MCP server (always-on scoring, no manual invocation, lock ownership)? (3) Is there a clean boundary between "batch processing" (script) and "query/serve" (MCP) that should be preserved? Decision needed: Consolidate vs. keep separate, with rationale. Suggested location: plugins/agentskill-kaizen/

SAM: Parser regex false positive on "## Task Summary Statistics"

Source: Migration proof-of-concept (2026-02-13) Added: 2026-02-13 Description: The widened task header regex ^#{2,3}\s+Task:?\s+([A-Za-z0-9.]+)[:\s-]+(.+)$ in implementation_manager.py matches ## Task Summary Statistics as task ID "Summary" with title "Statistics". The regex needs a negative lookahead or post-parse filter to exclude non-task sections. Observed when parsing plan/tasks-1-plugin-linter.md. File: plugins/python3-development/skills/implementation-manager/scripts/implementation_manager.py line 645

SAM: Replace validate-task-file.sh with Python validator

Source: Task format standardization plan (2026-02-13) Added: 2026-02-13 Description: The bash validator at plugins/plugin-creator/scripts/validate-task-file.sh validates a different schema (tasks-refactor-*.md) and doesn't understand YAML frontmatter. Replace with Python validator that uses the shared task_format.py module. File: plugins/plugin-creator/scripts/validate-task-file.sh

SAM: Parallel Execution Details

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Detail safe parallelization within SAM pipeline. When can tasks run in parallel? How to handle merge conflicts? Reference GSD wave execution pattern. Research first: How does GSD wave execution work in detail? How do task orchestrators (Temporal, Prefect) handle parallel dependencies? What conflict resolution patterns exist? Suggested location: stateless-software-engineering-framework.md (new section 2.4 or Appendix)

SAM: Multi-Model Strategy

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define guidance for using different models for different agent types. E.g., cheaper/faster models for simple verification, stronger models for planning. Research first: How do agent frameworks handle model selection? What cost/quality tradeoffs exist? How does Claude Code's haiku/sonnet/opus selection work? Suggested location: stateless-software-engineering-framework.md (Implementation Roadmap or new Appendix)

SAM: Audit Trail / Observability

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Beyond artifacts, define logging/metrics/tracing guidance. How to diagnose pipeline issues? What telemetry to capture? Research first: How do GSD and BMAD-METHOD handle logging? What observability patterns exist in agent frameworks? OpenTelemetry for LLM workflows? Suggested location: stateless-software-engineering-framework.md (new Appendix I)

SAM: Partial Success Handling

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define how to represent and handle partial task success. Task completes some DoD items but not all. How is this state represented in artifacts? Research first: How do GSD checkpoints represent partial progress? How do CI/CD systems handle partial test passes? What state machine patterns exist? Suggested location: stateless-software-engineering-framework.md (section 3.5 Execution Agent output)

SAM: Context Size Management

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define explicit guidance for measuring and managing context size per agent. What's the target token budget? How to detect context pressure? Research first: How do agent frameworks measure context usage? What token counting approaches exist? How does Claude Code handle context limits internally? Suggested location: stateless-software-engineering-framework.md (section 2.1 or Appendix C)

SAM: Conflicting Review Findings

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Define protocol when forensic review and self-verification disagree. Which takes precedence? How to adjudicate conflicts? Research first: How do code review systems handle conflicting reviewers? What adjudication patterns exist in multi-agent systems? How does GSD handle verification disagreements? Suggested location: stateless-software-engineering-framework.md (section 3.6 Forensic Review)

Multi-session build state lost during context compaction

Source: agentskill-kaizen plugin build (2026-02-18), 3 sessions with 1 compaction Added: 2026-02-18 Description: During the agentskill-kaizen build (8-phase /plugin-dev:create-plugin workflow), context compaction mid-build converted structured task state into a narrative summary. The resuming session had to reconstruct "what's done vs pending" from prose rather than a checklist. Background agent results that were already consumed and applied reappeared as late notifications after compaction, requiring manual deduplication ("did I already handle this?"). No persistent artifact tracked phase completion, commit SHAs per phase, deferred items, or agent result consumption status. Observed symptoms:

• Phase completion status existed only in ephemeral context — lost on compaction
• Background agent notifications arrived after their findings were already applied (3 duplicate notifications)
• Plan committed early (87a0b93) diverged from actual implementation but was never updated
• No mechanism to mark agent results as "consumed" — each notification required re-evaluation

/plugin-dev:create-plugin workflow lacks intra-phase parallelism tracking

Source: agentskill-kaizen plugin build (2026-02-18) Added: 2026-02-18 Description: The 8-phase create-plugin workflow treats each phase as a serial step, but Phase 5 (Implementation) actually consisted of 6 parallel sub-tasks and Phase 6 (Validation) spawned 3 parallel review agents. The workflow provides no structure for tracking parallel work within a phase — no task dependencies, no completion gates, no way to know which sub-tasks are done after compaction. Batching validation fixes by file rather than by finding would also have been more efficient (SKILL.md was edited 3 separate times when one pass would have sufficed).

Background agent result deduplication after compaction

Source: agentskill-kaizen plugin build sessions 2-3 (2026-02-18) Added: 2026-02-18 Description: Background agents launched in session N may complete after context compaction or session restart. The system delivers their results as <task-notification> messages, but there is no mechanism to mark results as already consumed. During the kaizen build, 3 review agents (plugin-validator, 2x skill-reviewer) completed during Phase 6 and their findings were applied in commit 0d61480. After compaction, all 3 re-delivered their notifications in session 3, requiring manual evaluation each time ("was this already handled?"). A persistent state file (e.g., .planning/kaizen/agent-results.json tracking task IDs → consumed/pending) would eliminate this waste.

/plugin-dev:create-plugin Phase 6 validation should batch fixes by file, not by finding

Source: agentskill-kaizen plugin build Phase 6 (2026-02-18) Added: 2026-02-18 Description: Phase 6 collected findings from 3 parallel review agents, then applied fixes one finding at a time. This resulted in SKILL.md being edited 3 separate times (description rewrite, SQL removal, MCP server name fix) when a single pass through the file would have applied all fixes together. The workflow should group all findings by file, then make one editing pass per file. Reduces Edit tool calls and context consumed by repeated reads.

Plan artifact diverges from implementation without update mechanism

Source: agentskill-kaizen plugin build (2026-02-18), plan committed as 87a0b93 Added: 2026-02-18 Description: The research/plan from Phase 2-3 was committed early as a markdown file. During implementation (Phase 5), decisions changed — the MCP server grew from planned scope, analysis dimensions were rebalanced, hook patterns shifted. The plan was never updated to reflect actual implementation. After compaction, the stale plan became a potential source of confusion. Two options to address: (1) update the plan artifact after each phase, or (2) treat the plan as disposable and track only the living state (what's done, what's pending, what deferred).

Evaluate scikit-learn dependency weight for agentskill-kaizen cluster_sessions tool

Source: agentskill-kaizen MCP server review (2026-02-18) Added: 2026-02-18 Description: The cluster_sessions tool in plugins/agentskill-kaizen/mcp/server.py uses scikit-learn (KMeans, CountVectorizer) for session clustering. scikit-learn pulls in ~40MB of transitive dependencies (numpy, scipy, joblib, threadpoolctl). The typical use case is clustering dozens of sessions, not thousands. The Phase 1-2 research produced no durable artifact evaluating library choices — scikit-learn was assumed from the backlog without validation. Investigate whether a lighter alternative (e.g., pyclustering, stdlib-based implementation, or just numpy directly) would suffice for this scale, and whether the KMeans-on-bag-of-words approach is even appropriate for tool-call sequence similarity. Research first: What clustering approaches work for short categorical sequences? Is cosine similarity on bag-of-words tool vectors meaningful for workflow comparison? What lightweight Python clustering libraries exist that don't pull in scipy?

Ideas

Configurable Token Thresholds for plugin_validator.py

Source: Session 2026-02-18, token threshold analysis Added: 2026-02-18 Description: plugin_validator.py token complexity thresholds (4400 warn, 8800 error) are hardcoded constants. Allow per-project or per-plugin configuration via a config file (e.g., .claude-plugin/validator.json or a [tool.plugin-validator] section in pyproject.toml) so different projects can set their own limits. Suggested location: plugins/plugin-creator/scripts/plugin_validator.py

SAM: Cost/Token Management

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Explore token budgets and cost controls per agent/stage. Track API costs. Set limits per task. Research first: How do LLM cost management tools work (LangSmith, Helicone)? What budget enforcement patterns exist?

SAM: Team Coordination Protocols

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Explore how multiple humans interact with the pipeline concurrently. Locking? Ownership? Notifications? Research first: How do collaborative editing systems handle concurrent users? What patterns exist in git-based workflows?

SAM: External System Integration Patterns

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Explore patterns for integrating with issue trackers (GitHub Issues, Jira), CI/CD pipelines, git hooks. Research first: How does GSD integrate with external tools? What MCP servers exist for issue trackers? How do agent frameworks bridge to CI/CD?

SAM: Migration Strategy Guide

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Explore how to migrate existing projects to SAM. Incremental adoption? Parallel running? Artifact bootstrap? Research first: How do organizations adopt new methodologies incrementally? What migration patterns exist for process changes?

SAM: Training/Onboarding Materials

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Explore creating materials for new team members learning the methodology. Tutorials, examples, quick-start guides. Research first: What training materials exist for GSD, BMAD-METHOD? What makes effective agent methodology onboarding?

SAM: Non-Code Workflow Guidance

Source: Gap analysis of SAM framework Added: 2026-02-01 Description: Explore how SAM handles documentation-only tasks, configuration changes, infrastructure work. Adapt templates? Research first: How do GSD and BMAD-METHOD handle non-code work? What artifact types exist beyond code?

Carbonyl Browser Integration for Claude Code

Source: Session experimentation 2026-02-05 Added: 2026-02-05 Description: Research whether carbonyl (terminal Chromium browser) can work with Claude Code for reliable web content extraction. Carbonyl renders pages in terminal but needs a TTY. Research areas:

• Can carbonyl run via tmux/screen/script to provide a pseudo-TTY?
• Could carbonyl be wrapped with a screenshot tool (e.g., termshot, asciinema) that passes images back to Claude?
• What's the minimal TTY setup needed for headless carbonyl operation?
• Compare with is-fast, lynx, w3m for text extraction capabilities Context: WebFetch is unreliable (summarizing agents hallucinate), Playwright requires browser downloads that may be blocked. Carbonyl is self-contained but needs TTY.

Validate is-fast for Web Content Extraction

Source: Session experimentation 2026-02-05 Added: 2026-02-05 Description: Test is-fast CLI tool on host with unrestricted network access. Validation steps:

• Install: curl --proto '=https' --tlsv1.2 -LsSf https://github.com/Magic-JD/is-fast/releases/latest/download/is-fast-installer.sh | sh
• Test: is-fast --direct https://code.claude.com/docs/en/skills --piped
• Verify it extracts text content from JS-rendered pages
• Compare output quality with curl, lynx, w3m
• Test CSS selector filtering with --selector Blocked on 2026-02-05: DNS resolution failed in restricted environment

Validate agent-browser for Web Automation

Source: Session experimentation 2026-02-05 Added: 2026-02-05 Description: Test agent-browser (Playwright-based) on host with unrestricted network and Playwright browsers installed. Validation steps:

• Install browsers: npx playwright install
• Test: npx agent-browser open https://code.claude.com/docs/en/skills
• Test: npx agent-browser snapshot -i (get element refs)
• Test: npx agent-browser get text body (extract page text)
• Verify snapshot/interact/re-snapshot workflow works
• Document prerequisites for skill to function Blocked on 2026-02-05: Could not download Playwright browsers (DNS resolution failed, missing system libs) Skill location: .claude/skills/agent-browser/SKILL.md

Validate carbonyl Terminal Browser

Source: Session experimentation 2026-02-05 Added: 2026-02-05 Description: Test carbonyl on host with proper TTY and network access. Validation steps:

• Test basic: npx -y carbonyl --no-sandbox https://example.com
• Test with tmux: tmux new-session -d -s carbonyl 'npx -y carbonyl --no-sandbox https://example.com'
• Test screenshot capture: Can we grab terminal output as image?
• Test text extraction: Can we pipe output or capture rendered text?
• Compare JS rendering quality with other tools Blocked on 2026-02-05: Needs TTY (Inappropriate ioctl for device), DNS also blocked

Completed

Resolve 48 pre-existing ty (Astral type checker) diagnostics

Source: uv run ty check . run during session 2026-02-11 Completed: 2026-02-19 Description: ty v0.0.16 reported 48 diagnostics. By v0.0.17 with existing extra-paths config, count dropped to 34 warnings (0 errors), all in plugins/agentskill-kaizen/tests/. Root causes: FastMCP @mcp.tool() decorator returns FunctionTool (ty sees as non-callable), and ModuleType dynamic attribute stubs. Suppressed call-non-callable and unresolved-attribute to "ignore" in test-file override scope. Added typecheck-ty CI job in allowed-failures for conservative rollout. Location: pyproject.toml ([tool.ty.overrides]), .github/workflows/code-quality.yml

Resolve plugin-validator pre-existing errors to make CI gate blocking

Source: CI pipeline run 22018867027 on claude/fix-ci-pipeline-RJ0Tw (2026-02-14) Completed: 2026-02-18 Description: Original 19 errors and 63 warnings (from 2026-02-14) were resolved across multiple prior sessions: LK001 broken links fixed, SK007 orchestrating-swarms split into 4 sub-skills, SK005 trigger phrase issues resolved. Final session fixed 4 remaining LK002 warnings in agentskills/SKILL.md (added ./ prefix) and promoted validate-plugins from allowed-failures to blocking in the quality gate. Location: plugins/plugin-creator/skills/agentskills/SKILL.md, .github/workflows/code-quality.yml Plan: plan/tasks-3-validator-ci-gate.md

Resolve manifest drift to make CI sync check blocking

Source: CI pipeline run 22018867027 on claude/fix-ci-pipeline-RJ0Tw (2026-02-14) Completed: 2026-02-18 Description: Ran auto_sync_manifests.py --reconcile to sync all 22 plugin.json manifests with on-disk skills, commands, and agents (153 drift entries fixed). Split the validate-plugins CI job into two: validate-plugins (plugin-validator, stays in allowed-failures) and manifest-sync (now blocking in quality gate). Version bumps applied to all affected plugins. Location: plugins/*/. claude-plugin/plugin.json, .github/workflows/code-quality.yml

Replace requests with httpx in all scripts

Source: CI/pre-commit inconsistency discovery (2026-02-05) Completed: 2026-02-06 Description: Migrated validate_glfm.py from requests to httpx. Added TID251 ruff ban rule for requests imports. Removed types-requests from dev dependencies. sync_gitlab_docs.py was already using httpx. Location: plugins/gitlab-skill/skills/gitlab-skill/scripts/validate_glfm.py, pyproject.toml

Enhance swarm-task-planner with multi-source synthesis

Source: external-pattern-integration-2026-02-01.md Completed: 2026-02-06 Description: Multi-source synthesis implemented via CLEAR+CoVe standard and Project Awareness section with investigation commands for searching documentation, assessing project structure, and identifying progress. Location: plugins/python3-development/agents/swarm-task-planner.md

Add context compliance checking

Source: external-pattern-integration-2026-02-01.md Completed: 2026-02-06 Description: Complete plan-validator agent implements 8 validation dimensions including Requirement Coverage, Task Completeness, Dependency Correctness, Agent Capability Match, Input/Output Validity, Artifact Wiring, Testability, and Scope Sanity. Location: plugins/python3-development/agents/plan-validator.md

SAM: Artifact Versioning Strategy

Source: Gap analysis of SAM framework Completed: 2026-02-06 Description: Implemented storage-agnostic semantic tokens using pattern ARTIFACT:{TYPE}({SCOPE_OR_ID}) with disambiguators (CTX, PREREQ, EXEC, VERIFY). Provides both filesystem-backed and SQL-backed example implementations. Location: stateless-software-engineering-framework.md (section 2.1.2)

Create ecosystem-researcher agent

Source: external-pattern-integration-2026-02-01.md Completed: 2026-02-05 Description: New agent for ecosystem/domain research before roadmap creation. Supports three modes - Ecosystem discovery, Feasibility assessment, Comparison analysis. Patterns from: gsd-project-researcher.md (research modes) Location: plugins/python3-development/agents/ecosystem-researcher.md

Format Guide

### Item title

**Source**: [link or description of where this came from]
**Added**: YYYY-MM-DD
**Description**: What needs to be done
**Research first**: (for SAM items) Questions to answer via competitive analysis before implementing
**Patterns from**: (optional) External source if from pattern integration
**Suggested location**: (optional) Where this should be implemented

Research Resources

Skill for research phase: /research-and-compare <methodology-name-or-url> (moved to stateless-agent-methodology repo)

• Produces structured comparison documents following SAM comparison template
• Includes overlap/divergence analysis, weakness discovery, implementation pairing
• Outputs to stateless-agent-methodology/.meta/v1_comparisons/

Existing SAM comparisons (start here before running new research):

• SAM v1 comparisons
  • sam-vs-get-shit-done.md
  • sam-vs-bmad-method.md
  • sam-vs-gastown.md
  • sam-vs-taskmaster.md
  • sam-vs-octocode.md
  • sam-vs-superclaude.md
  • sam-vs-ralph-loop-orchestrator.md
  • sam-vs-cc-sessions.md
  • sam-vs-v-model.md
  • sam-infrastructure-layer.md

Workflow for SAM gap items:

1. Check existing comparisons for relevant findings
2. If more research needed: /research-and-compare <framework> (in stateless-agent-methodology repo) for specific topics
3. Synthesize findings into SAM framework update
4. Mark backlog item complete

P1: plugin-validator pre-commit output is too noisy

Source: prek --all-files run during session 2026-02-15 Added: 2026-02-15 Description: Running prek --all-files produces pages of plugin-validator output — every file in the repo gets validated, and pre-existing warnings/errors (broken links, SK006 complexity, missing trigger phrases) for files unrelated to the current change drown out actionable information. The validator needs a review of its pre-commit integration to reduce noise. Observed symptoms:

• Full prek --all-files run produces hundreds of lines of validator output
• Pre-existing LK001 (broken links), SK006 (complexity warnings), SK005 (missing triggers) reported on every run
• FM003 (no frontmatter) fires on template files (commands/development/templates/*.md) that are not components — they're templates meant to be copied and filled in, not commands/skills/agents
• Difficult to find actual issues in changed files among the noise Related: "plugin-validator UX and coverage gaps" sub-issues below, "Resolve plugin-validator pre-existing errors to make CI gate blocking" backlog item File: plugins/plugin-creator/scripts/plugin_validator.py, .pre-commit-config.yaml

P1: plugin-validator UX and coverage gaps

Source: Experimental validation of plugin_validator.py against all component types (2026-02-13) Added: 2026-02-13 Last groomed: 2026-02-13 Plan: plan/tasks-2-validator-ux-coverage.md File: ./plugins/plugin-creator/scripts/plugin_validator.py (2934+ lines) Tests: ./plugins/plugin-creator/tests/ (12 test files, 93% pass rate per QA report) QA report: ./plugins/plugin-creator/planning/plugin-validator-qa-report.md

Sub-issue 1: UX — report counts validator results, not files

Severity: UX bug Lines: 2928-2931 (result collection loop), 2698-2702 (summary display)

Root cause: Lines 2928-2931 iterate over validators (not files), appending (path, result) for each validator. When 1 file has 4 validators (FrontmatterValidator, NameFormatValidator, DescriptionValidator, NamespaceReferenceValidator), the results list has 4 entries all pointing to the same path. The report loop at line 2630 then prints "PASSED" 4 times for 1 file, and the summary at line 2702 shows "Total files: 4".

Acceptance criteria:

• Running validator on 1 file shows "Total files: 1"
• Each validator result is labeled with the validator name (e.g., "FrontmatterValidator: PASSED")
• Summary counts unique files, not validator invocations

Sub-issue 2: Commands receive skill-specific SK005 warning

Severity: False positive Lines: 1884-1900 (SK005 check in DescriptionValidator), 2896-2901 (validator selection)

Root cause: DescriptionValidator.validate() (line 1802) has no file-type awareness. It applies SK004 ("description too short") and SK005 ("missing trigger phrases") to all file types. The validator selection at line 2896 applies DescriptionValidator to SKILL, AGENT, and COMMAND equally. Commands have a different frontmatter schema — they use argument-hint, allowed-tools, agent fields and do not need trigger phrases in their description.

Acceptance criteria:

• SK005 only fires on SKILL files (not COMMAND or AGENT)
• SK004 fires on SKILL and AGENT files (both need meaningful descriptions) but not COMMAND
• New error code series CM001+ for command-specific checks (e.g., validate allowed-tools format, argument-hint presence)
• DescriptionValidator receives file type context (via constructor parameter or path inspection)

Sub-issue 3: Hooks have zero validation

Severity: Missing feature Lines: 148-165 (detect_file_type returns UNKNOWN for .js hooks and hooks.json)

Root cause: FileType enum (line 141-145) has no HOOK variant. detect_file_type() only matches SKILL.md, plugin.json, agents/, commands/. Hook files (.js in hooks/ directories, hooks.json configs) fall through to UNKNOWN, which triggers the error at line 2920.

Acceptance criteria:

• FileType enum includes HOOK_SCRIPT and HOOK_CONFIG (or combined HOOK)
• detect_file_type() recognizes .js files in hooks/ directories
• detect_file_type() recognizes hooks.json files
• New error code series HK001+ for hook validation (e.g., valid JSON in hooks.json, valid event types, valid hook matcher patterns)
• New HookValidator class following existing Validator protocol
• Reference: /plugin-creator:claude-hooks-reference-2026 skill for hooks.json schema

Sub-issue 4: Dead code — nested skill resolution pattern

Severity: Code quality Lines: 904-911 (in _resolve_skill_reference method of NamespaceReferenceValidator)

Root cause: Lines 904-911 search for plugins/{plugin}/skills/*/{name}/SKILL.md (nested category pattern). This pattern does not exist in the repository. Actual skill layout is plugins/{plugin}/skills/{name}/SKILL.md (flat). The direct check at lines 899-902 handles all real cases. The nested search at 904-911 is dead code. Additionally, lines 759-760 and 771-772 reference the nested pattern in error message strings.

Note: The original backlog item referenced lines 651-656 and 778-785 as dead code for _discover_skills and _discover_invocable_skills. Those methods do not exist in the current source. The actual dead code is in _resolve_skill_reference at lines 904-911.

Acceptance criteria:

• Remove lines 904-911 (nested skill resolution)
• Update error message strings at lines 759-760 and 771-772 to remove nested pattern references
• Verify no test depends on nested skill resolution (grep tests for skills/*/ double-nested patterns)

Dependencies

• Sub-issues 1-4 are independent and can be implemented in parallel
• Sub-issue 3 (hooks) is the largest — requires new FileType, new Validator class, new error codes
• Sub-issue 2 (command SK005) requires deciding on a command-specific error code series

Related prior work

• QA report documents 15 pre-existing test failures (93% pass rate) — check for conflicts before modifying validators
• /plugin-creator:claude-hooks-reference-2026 — hooks.json schema reference for sub-issue 3
• /plugin-creator:claude-skills-overview-2026 — skill vs command schema differences for sub-issue 2

Approach

Use /python3-development:add-new-feature to extend plugin_validator.py. Delegate implementation to @python-cli-architect. Each sub-issue is a separate task.