planner-rt-ica
Runs information completeness pre-pass before task decomposition and plan generation. Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios. Localizes missing inputs to affected tasks only — does not block plan generation. Produces completeness summary (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, or BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations for downstream tasks. Non-blocking sister to dh:rt-ica — use dh:rt-ica at the S2 implementation gate where missing inputs must halt execution.
58
67%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/development-harness/skills/planner-rt-ica/SKILL.mdQuality
Discovery
85%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong, detailed description that clearly articulates what the skill does and when to use it, with explicit trigger guidance and well-defined outputs. Its main weakness is the use of specialized jargon and internal references (dh:rt-ica, S2 implementation gate) that may not match natural user language. The description is distinctive and unlikely to conflict with other skills due to its narrow, well-defined niche.
Suggestions
Add more natural-language trigger terms that users might actually say, such as 'check requirements completeness', 'missing information', 'do I have enough detail to plan', or 'requirements gaps'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | 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. | 3 / 3 |
Completeness | Clearly answers both 'what' (runs information completeness pre-pass, produces completeness summary, missing input report, dependency mapping, unblock actions, planning annotations) and 'when' (explicit 'Use when' clause covering grooming backlog items, generating plans, decomposing tasks under uncertainty, brownfield/refactor scenarios). Also distinguishes from a sister skill for additional clarity. | 3 / 3 |
Trigger Term Quality | Includes some relevant terms like 'grooming backlog items', 'generating plans', 'decomposing tasks', 'brownfield', 'refactor scenarios', but many are somewhat specialized/jargon-heavy. Terms like 'dh:rt-ica' and 'S2 implementation gate' are internal references unlikely to match natural user language. Missing simpler variations a user might say like 'check if I have enough info' or 'missing requirements'. | 2 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: pre-planning information completeness analysis. The specific output statuses, the non-blocking nature, and the explicit differentiation from the sister skill 'dh:rt-ica' make it very unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-conceived planning-phase skill with clear domain-specific value, particularly the localized-gaps approach and the data-deletion hard-block rule. Its main weaknesses are the lack of concrete examples showing actual output (e.g., a sample completeness summary or missing-inputs report), and the somewhat implicit workflow that could benefit from explicit step-by-step sequencing. Some philosophical content and redundant explanations could be trimmed to improve token efficiency.
Suggestions
Add a concrete example showing a complete output: a sample completeness summary, missing inputs table, unblock actions, and planning annotations for a realistic scenario — this would significantly improve actionability.
Add an explicit numbered workflow sequence (e.g., '1. Receive planning scope → 2. Enumerate inputs → 3. Classify each as PRESENT/PARTIAL/MISSING using reflection checkpoint → 4. Map dependencies → 5. Emit structured output') to improve workflow clarity.
Trim the Complexity Model section to its core insight ('Step boundaries follow knowledge boundaries, not implementation boundaries') and the 'Well-lit trail' principle to a single sentence — these are currently verbose for the value they add.
Consider extracting the Complexity Model mermaid diagram and the detailed behavioral rules into a referenced file to improve progressive disclosure for this longer skill.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | 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. | 2 / 3 |
Actionability | The skill provides structured output contracts and behavioral rules, which give concrete guidance on what to produce and how to behave. 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 guidance is specific but remains at the template/description level rather than copy-paste ready. | 2 / 3 |
Workflow Clarity | The skill describes a clear sequence (pre-pass → analysis → output sections → downstream annotations) and includes the important data-deletion hard-block rule as a validation checkpoint. However, the overall workflow is implicit rather than explicitly sequenced — there's no numbered step-by-step process for running the analysis. The reflection checkpoint using sequential-thinking MCP is a good validation step, but the overall flow from 'receive planning scope' to 'emit completeness report' lacks explicit sequencing with clear checkpoints. | 2 / 3 |
Progressive Disclosure | The content is well-organized with clear section headers and logical grouping. However, for a skill of this length (~180 lines of substantive content), some sections like the Complexity Model mermaid diagram and the detailed behavioral rules could be split into referenced files. There are no bundle files and no references to external documents, so everything is inline. The structure is good but the skill is somewhat monolithic. | 2 / 3 |
Total | 8 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- Jamie-BitFlight/claude_skills
- Commit
4e61312
- Reviewed
Table of Contents
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