Conciseness

The body is dense and imperative — commands, templates, and tables with almost no conceptual explanation of things Claude already knows. Only minor tightening is possible: the custom-story rule 'At least 1. Each tests a distinct regression hypothesis' is stated twice in Step 0c, and the 'unverified' handling is explained both in Step 1b and again in Step 5. That fits anchor 4 ('efficient; minor instances of over-explanation that could be trimmed') rather than anchor 5's every-token-earns-its-place.

Actionability

Nearly everything is copy-paste executable: full `uv run` bash commands, working python3 snippets for parsing both Gemini JSON and Claude JSONL sessions, a complete custom-story YAML template, a concrete scoring matrix, and an exact report table schema with a filled-in example row. Placeholders like `<first_story>` and `<baseline>` are explicitly bound to parsed arguments, matching anchor 5 ('fully executable; copy-paste ready code or commands').

Workflow Clarity

Steps 0-8 are strictly ordered with each consuming the prior step's output, verification is mandated after every story ('ALWAYS verify each story via ha_query.py before running the next'), and error feedback loops are explicit: failed verification queries are re-run then recorded as 'unverified', regressions trigger re-run/flakiness handling via the referenced protocol, and token outliers route to a KV-cache investigation step. This matches anchor 5 ('explicit validation steps; feedback loops for error recovery').

Progressive Disclosure

Both bundle references exist (`references/evaluation-protocol.md`, `references/regression-protocol.md`) and are clearly signaled with purposes in the Key Files table, plus one inline pointer in Step 1b — one level deep, no nesting. However, the Step 4 scoring matrix and the white-box criteria partially duplicate the evaluation protocol reference, and the ~375-line body could push the scoring-matrix detail out to it. That fits anchor 4 ('good structure; most content appropriately placed; minor organization gaps') rather than anchor 5's clean split.

Specificity

The description names the domain ("MCP tool behavior between target and baseline versions") and 1-2 concrete actions ("Compare ... using pre-built and custom stories with diff-based triage"), but stops there — no mention of scoring, regression detection, or reporting. This matches anchor 3 ('names domain and 1-2 concrete actions, but not comprehensive') better than anchor 4, which expects several listed actions with only minor coverage gaps.

Completeness

The 'what' is clear — compare MCP tool behavior across versions with story-based triage — but there is no 'when' clause at all; the description never states when Claude should invoke it. Per the judging guidelines, a missing 'Use when...' clause or equivalent explicit trigger guidance caps completeness at 3, which this squarely matches.

Trigger Term Quality

Relevant keywords exist ("MCP tool behavior", "baseline", "diff-based triage") but the natural phrases a user would actually say are missing (e.g., "compare versions", "check for regressions", "A/B test the MCP server"). Terms like "pre-built and custom stories" and "diff-based triage" are internal jargon rather than user-facing triggers, fitting anchor 3 ('some relevant keywords but missing common variations or synonyms') and not anchor 4's 'good keyword coverage'.

Distinctiveness Conflict Risk

The niche is quite specific — A/B comparison of MCP tool behavior between git versions via story runs — so overlap with generic testing/eval skills is minor. It falls just short of anchor 5's 'distinct triggers' because the description provides no explicit trigger phrases that would reliably route invocation to it over a neighboring regression-testing skill.