Conciseness

Mostly operational and efficient, but there is measurable redundancy: the WhaleWisdom/SEC EDGAR/DataRoma list appears twice (Step 3 and the track_institution_portfolio.py section), "Screening workflow integration" in Step 5 duplicates the "Integration with Other Skills" section, and the "Why coverage, not per-holder reconciliation" paragraph is API-rationale detail that could be trimmed or moved to a reference. Not a 2 because none of it is generic padding or explanation of concepts Claude already knows; not a 4 because the duplication is more than minor.

Actionability

Concrete, copy-paste-ready commands throughout — quick scan, sector scan, custom screening, single-stock deep dive — with full parameter documentation, defaults, output formats, and quantified interpretation thresholds (>15% QoQ, top-10 >50% concentration). Not a 5 because of a minor gap: the Step 3 example invokes "python3 institutional-flow-tracker/scripts/analyze_single_stock.py AAPL" while every other command uses "scripts/...", so one example is not executable as written from the skill directory.

Workflow Clarity

A clearly sequenced 5-step workflow with most checkpoints present: each step's output is specified, and data validation is built in via the A/B/C reliability grades with automatic Grade-C exclusion from screening. Not a 5 because there are no explicit error-recovery loops (e.g., what to do when the API key is missing, rate-limited, or a ticker returns no data); not a 3 because validation checkpoints are explicit and prominent rather than implicit.

Progressive Disclosure

Good structure against the actual bundle: the three reference files exist, are one level deep, and are clearly signaled twice (Step 4 and the References section with per-file descriptions); scripts and their parameters are documented inline. Not a 5 because the SKILL.md is a ~380-line body carrying substantial interpretive bulk — the full Signal Strength Framework, Limitations, and Advanced Use Cases — that overlaps the interpretation_framework.md reference and could be split out.

Specificity

Lists several concrete actions — "track institutional investor ownership changes and portfolio flows using 13F filings data", "Analyzes hedge funds, mutual funds, and other institutional holders", "identify stocks with significant smart money accumulation or distribution", "discover stocks before major moves". Not a 5 because coverage has minor gaps: no mention of the screening commands, quarterly report generation, or sector filtering that the skill actually provides.

Completeness

Both what and when are present: the opener "Use this skill to track institutional investor ownership changes..." is explicit trigger guidance, and the what is detailed across three sentences. Not a 5 because the when restates the what rather than naming distinct user scenarios (e.g., "Use when the user asks about hedge fund positions or 13F filings"); not a 3 because the "Use this skill to..." clause is equivalent explicit trigger guidance, so the missing-'Use when' cap does not bind.

Trigger Term Quality

Good natural keyword coverage: "institutional investor", "13F filings", "hedge funds", "mutual funds", "smart money", "accumulation or distribution", "ownership changes". Falls short of comprehensive because common variations like "institutional buying/selling", "SEC filings", "fund holdings", or "13Fs" are absent.

Distinctiveness Conflict Risk

Clear niche with distinct triggers — "13F filings" and "institutional investor ownership changes" are unlikely to fire the wrong skill. Minor overlap risk remains: "portfolio flows" could collide with portfolio-management skills, and within a finance skill suite the generic "analyze" framing slightly overlaps sibling screeners.