Conciseness

The body is operational and free of concept explanations — sections like Export Rules ('Keep `validation.method: full_sample`') and Guardrails state only what to do. Minor trimming is possible: the Resources section re-lists script and reference paths already given in the Workflow section, and 'When to Use' restates the frontmatter description. This fits the 4 anchor ('minor instances of over-explanation that could be trimmed') better than the lean-every-token-earns-its-place 5 anchor.

Actionability

Four copy-paste-ready bash commands with realistic flags and paths cover the common cases — daily auto-detection (--ohlcv, --hints, --export-strategies-dir), export from a ticket, interface-only validation, and full validation with --pipeline-root/--stage. Concrete rules and guardrails ('Reject candidate when folder name and `id` mismatch') add executable specificity, matching the 5 anchor.

Workflow Clarity

The six-step workflow is clearly sequenced (auto-detect, load references, build ticket, export, validate, handoff) with explicit validation checkpoints (validate_candidate.py at step 5, 'Use `--dry-run` in pipeline before full execution') — so the missing-validation cap of 3 does not apply. However, no explicit error-recovery feedback loop is stated (e.g., 'if validation fails, review reasons, fix the ticket, and re-export'), which keeps it at the 4 anchor rather than 5.

Progressive Disclosure

The body is a lean overview and all details are split into four real, one-level-deep reference files (pipeline_if_v1.md, signal_mapping.md, research_ticket_schema.md, ideation_loop.md) and three real scripts, each clearly signaled in Workflow step 2 and in the Resources section with one-line descriptions. Verified against the actual bundle structure — no nesting or dead references — matching the 5 anchor.

Specificity

Lists multiple concrete actions — 'Generate and prioritize US equity long-side edge research tickets from EOD observations', 'export pipeline-ready candidate specs for trade-strategy-pipeline Phase I', 'preflight-check interface compatibility (`edge-finder-candidate/v1`)' — with concrete artifacts (`strategy.yaml` + `metadata.json`), matching the comprehensive-coverage anchor. The 4 anchor ('minor gaps in coverage') fits worse since ticket generation, prioritization, export, and preflight validation are all explicitly named.

Completeness

Explicitly answers both 'what' ('Generate and prioritize US equity long-side edge research tickets... export pipeline-ready candidate specs for trade-strategy-pipeline Phase I') and 'when' ('Use when users ask to turn hypotheses/anomalies into reproducible research tickets, convert validated ideas into strategy.yaml + metadata.json, or preflight-check interface compatibility... before running pipeline backtests') with concrete trigger phrases — a clear match for the 5 anchor. The 4 anchor requires a less explicit 'when', which does not apply.

Trigger Term Quality

Good keyword coverage with natural trigger phrasings ('turn hypotheses/anomalies into reproducible research tickets', 'convert validated ideas into strategy.yaml + metadata.json', 'before running pipeline backtests') including synonyms (hypotheses/anomalies/ideas) and file names. A few natural terms for the detection half of the skill (e.g., 'discover new edge', 'daily detection', 'watchlist', 'OHLCV') are missing, so it falls short of the 5 anchor's comprehensive coverage.

Distinctiveness Conflict Risk

A clear niche with distinct triggers: 'US equity long-side edge research tickets', 'trade-strategy-pipeline Phase I', and the pinned interface version '`edge-finder-candidate/v1`' are unlikely to fire for unrelated skills. It is well above the 4 anchor, whose 'minor overlap risk with closely related skills' is only marginally arguable given sibling skills in the split workflow.