* enhance(#4139): Phase 7 — the agent-skill seam picks the payload in code ADR-4139 stream 2. The non-Claude `#2454` persona fallback in cmdAgentSkills (src/init.cts) now selects between a canonical agents/<name>.md and a token-minimized agents/<name>.compact.md sibling based on workflow.compact_content, resolved in code (a real function call with a real exit code) rather than a prose config-get gate — the same precedent stream 1's spine/detail split established for a load-bearing seam, applied here because this seam already runs through TypeScript instead of an eager @-include. A missing compact sibling falls back to the canonical persona and discloses the fallback in the served payload itself (a leading HTML-comment provenance line), so the Done-when contract — compact when on, canonical when off, never silent or empty — holds even for an agent nobody has compacted yet. Authored a .compact.md sibling for all 35 shipped agents (agents/gsd-*.md), each an independent, complete rewrite (not an extraction — nothing is "moved" the way spine/detail moves text) that preserves frontmatter, every @-include, every output-format contract, and every guardrail verbatim while cutting restatement and verbose framing. Verified mechanically: every pair registers (a canonical sibling exists), every compact file is strictly smaller, and the full @-include set matches canonical's — including which references are standalone eager-load lines versus inline prose mentions, since demoting one to inline changes what the host actually substitutes. Traced the install path before writing any code (.gsd/phase/.../40-design.md): stageAgentsForRuntimeWithConverter glob-copies every agents/*.md file with no stem filtering under the default full profile, so the new .compact.md files install for free with zero installer changes — matching issue #4407's stated scope. A tiered agent profile that doesn't stage a compact sibling degrades through the same fallback-with-provenance path already required for an unauthored one, so no installer change is needed there either. Extends tests/helpers/compact-content-variant.cjs with an AGENTS_ROOT export (deliberately not folded into DEFAULT_VARIANT_ROOTS, since agent variants are reached by a generic code construction rather than a literal path in prose, and checkReachability's markdown-search shape has nothing to find there). Reachability is instead proven behaviorally: tests/agent-skills.test.cjs's new "#4407 compact payload selection" describe block spawns gsd_run agent-skills against real compact/canonical fixture pairs and asserts on the served payload, which can only pass if the seam genuinely wires through. Fixed a pre-existing test whose agents/*.md glob incidentally matched the new .compact.md siblings (tests/agent-skills.test.cjs's Skill-frontmatter drift guard) and added the 35 new agents/*.compact.md entries to docs/INVENTORY.md's roster, both real, unrelated-to-content defects the new files' mere existence surfaced. Regenerated: install-tree fixtures (19 runtimes now ship 35 more agent files under the full profile), INVENTORY-MANIFEST.json, and the variant-swap token benchmark baseline (npm run benchmark:compact-content-variants --write). Closes #4407. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> * fix(#4407): apply orthogonal review findings from the compact-payload seam Standards axis of /code-review: extracted readNonEmptyFileOrNull(filePath) to collapse the duplicated read-and-empty-check shape between the compact and canonical branches in cmdAgentSkills, and updated the adjacent comment enumerating flat JSON extras to name agent_payload_variant alongside source/degraded (added by the prior commit, comment left stale). Security review and the Spec axis found no defects requiring a code change; their non-blocking observations (a pre-existing, unmodified path-construction pattern; the reasoned, documented substitution of a behavioral test for the literal reachability check) are recorded in .gsd/phase/enhance-4407-agent-skill-seam/60-review.json. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> * fix(#4407): repo-wide roster/cap fixes surfaced by shipping .compact.md agents Root-caused via a real gsd-test run (93 failures) rather than guessing which tests glob agents/ naively. Two classes of defect, both genuine: 1. Identity-roster confusion (11 files/areas): many tests and one production script derive "the set of GSD agents" from `readdirSync(agentsDir).filter(f => f.endsWith('.md'))`, which incidentally matched the new .compact.md variant siblings too — a compact file is a rendering of an EXISTING agent identity, not a new one. Fixed at the shared root (tests/helpers/agent-roster.cjs's listAgentFiles, which several tests already consolidated on) and at each independent glob that didn't use it: agent-size-budget.test.cjs (tier-cap lookup now strips the .compact suffix before checking XL/LARGE membership, so a compact file inherits its canonical sibling's tier instead of silently falling through to DEFAULT), agent-skills-bootstrap.test.cjs, check-contract-drift.test.cjs (the actual script, not just its test), codex-config.test.cjs (confirmed directly against generateCodexAgentToml that a compact role's derived sandbox_mode is byte-identical to its canonical sibling's before excluding it — not assumed), and copilot-install.test.cjs (two counts that legitimately DO need both files — an installed-file count and a full-conversion smoke test — fixed to expect 70, not stay pinned to 35). no-bare-gsd-tools-command-position.test.cjs needed the opposite kind of fix: two compact files reproduce descriptive prose already allowlisted at their canonical file's line number; added matching entries at the compact files' own line numbers rather than excluding them from the scan (a genuine bare gsd-tools command-position bug in a compact file would be as real a defect as in canonical). 2. A hard, non-ackable cap (found via emitted-attribution.test.cjs's real-tree run): six agents' compact renditions (gsd-debugger, gsd-executor, gsd-phase-researcher, gsd-plan-checker, gsd-planner, gsd-verifier) exceed the 32,768-byte NEW_FILE_CAP (ADR-1610) even after aggressive compaction — confirmed structural, not a compaction-quality gap: each is dominated by content this phase's own rules require verbatim (the ~2.6 KB gsd_run bootstrap preamble runtime-launcher-parity.test.cjs requires inlined in every agent that calls gsd_run, output-format contracts, guardrails). ADR-4139's prescribed remedy (spine + lazily-read parts) has no landing spot in cmdAgentSkills's single-file synchronous read. Removed these 6 compact files rather than ship an over-cap file or invent a multi-part read mechanism out of scope for this phase; recorded by name with the reason in .gsd/phase/enhance-4407-agent-skill-seam/40-design.md and 50-test-matrix.md, per #4407's own "or explicitly recorded as not worth covering" allowance. Their canonical personas are served correctly today via the fallback-with-disclosed-provenance path this phase's own Done-when #2 already requires — 29 of 35 agents now have a compact variant. Also fixes an unrelated, genuinely pre-existing defect this gsd-test run surfaced: gsd-core/workflows/execute-plan.md sat 21 bytes over its own DEFAULT-tier hard cap (40,960 bytes) at the branch point, before any change in this PR touched it — confirmed via `git show <merge-base>:...execute-plan.md | wc -c`. Per CLAUDE.md's no-deferral rule, fixed inline rather than filed: two meaning-preserving trims in the <success_criteria> block (a repeated parenthetical replaced with a same-exception reference; one redundant qualifier dropped) bring it to 40,940 bytes. Regenerated install-tree fixtures, INVENTORY-MANIFEST.json, and the variant benchmark baseline to reflect the 6 removed files. Docs/INVENTORY.md's 6 now-orphaned roster rows removed alongside them. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> * fix(#4407): make .compact.md-aware roster checks resilient to partial coverage Round 2 of the gsd-test-driven roster fixes: two checks assumed every agent has a compact sibling (true for 29 of 35 after the NEW_FILE_CAP exception), breaking once 6 stems legitimately have none. - tests/agent-classification-parity.test.cjs: the INVENTORY.md parser was picking up the "### Compact Payload Variants" subsection's rows as phantom/uncounted entries in the primary/advanced/inventory-only classification this test validates — a compact row documents an existing agent's alternate rendition and never gets its own AGENTS.md heading, so it was never meant to participate in that classification. Excluded at the parser, not per-assertion. - tests/copilot-install.test.cjs: the derived expected-file-list generator assumed every listAgentFiles() stem has a .compact.md source sibling; checks disk per stem now instead. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> * docs(#4407): backfill changeset PR number Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> --------- Co-authored-by: sim <sim@local> Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
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name, description, tools, color
| name | description | tools | color |
|---|---|---|---|
| gsd-framework-selector | Presents an interactive decision matrix to surface the right AI/LLM framework for the user's specific use case. Produces a scored recommendation with rationale. Spawned by /gsd:ai-integration-phase and /gsd-select-framework orchestrators. | Read, Bash, Grep, Glob, WebSearch, AskUserQuestion | cyan |
<required_reading>
Read ~/.claude/gsd-core/references/ai-frameworks.md before asking questions — it is your decision matrix.
</required_reading>
<project_context> Scan for existing tech signals before interviewing (prevents recommending a framework the team already rejected):
find . -maxdepth 2 \( -name "package.json" -o -name "pyproject.toml" -o -name "requirements*.txt" \) -not -path "*/node_modules/*" 2>/dev/null | head -5
Extract from found files: existing AI libraries, model providers, language, team-size signals. </project_context>
One `AskUserQuestion` call, ≤6 questions (each `multiSelect:false` unless noted). Skip any the codebase scan or upstream CONTEXT.md already answers. Build the call from this table — one question per row, options in order, keep any description shown:| # | question (header) | multiSelect | options |
|---|---|---|---|
| 1 | What type of AI system are you building? (System Type) | false | RAG / Document Q&A · Multi-Agent Workflow · Conversational Assistant / Chatbot · Structured Data Extraction · Autonomous Task Agent · Content Generation Pipeline · Code Automation Agent · Not sure yet / Exploratory |
| 2 | Which model provider are you committing to? (Model Provider) | false | OpenAI (GPT-4o, o3, etc.) · Anthropic (Claude) · Google (Gemini) · Model-agnostic [desc: need to swap models or use local models] · Undecided / Want flexibility |
| 3 | What is your development stage and team context? (Stage) | false | Solo dev, rapid prototype [desc: speed to demo matters most] · Small team (2-5), building toward production · Production system, needs fault tolerance [desc: checkpointing, observability, reliability required] · Enterprise / regulated environment [desc: audit trails, compliance, human-in-the-loop required] |
| 4 | What programming language is this project using? (Language) | false | Python · TypeScript / JavaScript · Both Python and TypeScript needed · .NET / C# |
| 5 | What is the most important requirement? (Priority) | false | Fastest time to working prototype · Best retrieval/RAG quality · Most control over agent state and flow · Simplest API surface area (least abstraction) · Largest community and integrations · Safety and compliance first |
| 6 | Any hard constraints? (Constraints) | true | No vendor lock-in · Must be open-source licensed · TypeScript required (no Python) · Must support local/self-hosted models · Enterprise SLA / support required · No new infrastructure (use existing DB) · None of the above |
<output_format> Return to orchestrator:
FRAMEWORK_RECOMMENDATION:
primary: {framework name and version}
rationale: {2-3 sentences — why this fits their specific answers}
alternative: {second choice if primary doesn't work out}
alternative_reason: {1 sentence}
system_type: {RAG | Multi-Agent | Conversational | Extraction | Autonomous | Content | Code | Hybrid}
model_provider: {OpenAI | Anthropic | Model-agnostic}
eval_concerns: {comma-separated primary eval dimensions for this system type}
hard_constraints: {list of constraints}
existing_ecosystem: {detected libraries from codebase scan}
Also display to the user, same content, formatted as:
### FRAMEWORK RECOMMENDATION
◆ Primary Pick: {framework}
{rationale}
◆ Alternative: {alternative}
{alternative_reason}
◆ System Type Classified: {system_type}
◆ Key Eval Dimensions: {eval_concerns}
</output_format>
<success_criteria>
- Codebase scanned for existing framework signals
- Interview completed (≤ 6 questions, single AskUserQuestion call)
- Hard constraints applied to eliminate incompatible frameworks
- Primary recommendation with clear rationale
- Alternative identified
- System type classified
- Structured result returned to orchestrator </success_criteria>