Lists multiple specific concrete actions: runs completeness pre-pass, produces completeness summary with named statuses (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations. Very detailed about outputs.

Clearly answers both 'what' (runs information completeness pre-pass, produces completeness summary, missing input report, unblock actions, planning annotations) and 'when' (explicit 'Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios'). Has an explicit 'Use when...' clause.

Includes natural trigger terms users would say: 'grooming backlog items', 'generating plans', 'decomposing tasks', 'uncertainty', 'brownfield', 'refactor scenarios'. Also includes the skill identifier 'dh:rt-ica' for disambiguation. These are terms a user working in project planning and task management would naturally use.

Highly distinctive — clearly scoped to pre-planning information completeness checks, explicitly differentiates itself from its sister skill 'dh:rt-ica' (which is for the implementation gate), and uses unique status labels (APPROVED-FOR-PLANNING, etc.) that define a clear niche unlikely to conflict with other skills.

The skill is reasonably well-structured but includes some verbose explanations that Claude doesn't need — e.g., the 'Complexity Model' section explaining what project-specific knowledge is vs training data, and the philosophical 'Well-lit trail, not locked gates' principle. The sister-skill comparison table and relationship section are somewhat redundant with each other. However, most content is domain-specific and not trivially known.

The skill provides structured output contracts and behavioral rules, which give concrete guidance on what to produce. However, it lacks executable examples — no sample input/output showing what an actual completeness summary, missing inputs report, or planning annotation looks like in practice. The instructions are specific but remain at the template/description level rather than showing concrete filled-in examples.

The workflow is clearly sequenced: run as pre-pass → analyze inputs → produce completeness summary → emit missing inputs with dependency mapping → generate unblock actions → apply planning annotations downstream. Validation is addressed through the reflection checkpoint (sequential-thinking MCP call), the data deletion hard-block rule, and the explicit requirement that APPROVED-WITH-GAPS tasks must still pass rt-ica before execution. Feedback loops are present (redirect unsourced values, re-classify).

The content is well-organized with clear section headers and logical flow. However, it's a fairly long monolithic document (~180 lines of substantive content) with no references to supporting files. The Mermaid diagram for the complexity model and the detailed behavioral rules could be split into referenced files. Given no bundle files exist, the skill could benefit from better content splitting.