plugins/development-harness/skills/planner-rt-ica/SKILL.md
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.
npx skillsauth add jamie-bitflight/claude_skills planner-rt-icaInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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| If you are… | Load |
|---|---|
| Grooming a backlog item, generating a plan, decomposing tasks under uncertainty | dh:planner-rt-ica (this skill — non-blocking) |
| At the S2 implementation gate where missing inputs must halt the pipeline | dh:rt-ica (the blocking sister skill) |
dh:planner-rt-ica and dh:rt-ica are deliberately split: same framework, different cost-of-being-wrong. During planning, a MISSING condition is a research task. At the implementation gate, the same MISSING is a halt event because the agent would otherwise guess. Do not consolidate.
This skill adapts RT-ICA for planning contexts.
Its purpose is NOT to block planning. Its purpose is to prevent invented requirements while still allowing a correct dependency-first plan to be produced.
This skill runs as a pre-pass before task decomposition and task writing.
Task complexity is the ratio of project-specific knowledge required to context window available — not implementation difficulty.
Training data covers craft knowledge (language patterns, tooling, frameworks). That is free. What consumes context budget is project-specific knowledge: schemas, pin-outs, conventions, power constraints, existing interfaces, user preferences. This knowledge must be loaded before an agent can act.
The planner should use this when sizing tasks:
flowchart TD
Conditions["Conditions from RT-ICA"] --> Estimate["For each task: estimate how much<br>project-specific context the executor<br>must load to satisfy its conditions"]
Estimate --> Shared{Do multiple tasks<br>need the same<br>knowledge loaded?}
Shared -->|Yes| Combine["Combine into one task —<br>knowledge loaded once,<br>both steps execute in<br>remaining window space"]
Shared -->|No| Size{Knowledge payload<br>vs context window?}
Size -->|"Fits with room to work"| Single["Single task"]
Size -->|"Leaves little room"| Split["Decompose along<br>knowledge boundaries —<br>each subtask needs a<br>smaller knowledge subset"]
Combine --> Annotate
Single --> Annotate
Split --> Annotate
Annotate["Annotate each task with<br>its knowledge requirements<br>so the executor knows<br>what to load"]
Step boundaries follow knowledge boundaries, not implementation boundaries. Two steps sharing the same knowledge payload should be one task. A step requiring a distinct, large knowledge set deserves its own agent and context window.
No invention
Localize uncertainty
Plan must still exist
Execution safety
Well-lit trail, not locked gates
For the given planning scope (entire plan or a specific task/workstream), identify whether the following are PRESENT, PARTIAL, or MISSING:
Produce a structured analysis with the following sections:
APPROVED-WITH-GAPS is the expected and normal outcome for brownfield, refactor, and discovery scenarios.
For each missing or partial input, emit:
For each missing input, specify one of:
These MUST be expressible as planner tasks.
The planner MUST apply the following annotations downstream:
When this skill reports missing inputs:
The planner MUST:
When the planner catches itself generating an unsourced value or constraint:
Data Deletion Fidelity is not a gap — it is a hard block. When the planning scope describes a task that deletes source data AND the acceptance criteria lack a content completeness check against real production data: do NOT classify this as APPROVED-WITH-GAPS; do NOT emit unblock tasks and proceed; emit BLOCKED-FOR-PLANNING with the reason: "Task deletes source data without a real-data fidelity gate. Add: (1) content completeness assertion against real production records, (2) explicit deletion gate requiring zero-data-loss confirmation before deletion is permitted." This rule takes precedence over the general APPROVED-WITH-GAPS path. Data loss is not a gap that can be resolved later — it is irreversible.
This skill does NOT replace rt-ica.
planner-rt-ica:
rt-ica:
Any task produced under APPROVED-WITH-GAPS MUST still pass rt-ica
before being executed by a specialist agent.
This skill is successful if:
development
When an application needs to store config, data, cache, or state files. When designing where user-specific files should live. When code writes to ~/.appname or hardcoded home paths. When implementing cross-platform file storage with platformdirs.
testing
Enforce mandatory pre-action verification checkpoints to prevent pattern-matching from overriding explicit reasoning. Use this skill when about to execute implementation actions (Bash, Write, Edit) to verify hypothesis-action alignment. Blocks execution when hypothesis unverified or action targets different system than hypothesis identified. Critical for preventing cognitive dissonance where correct diagnosis leads to wrong implementation.
tools
Reference guide for the Twelve-Factor App methodology — 15 principles (12 original + 3 modern extensions) for building portable, resilient, cloud-native applications. Use when evaluating application architecture, designing cloud-native services, reviewing codebases for methodology compliance, advising on configuration, scaling, observability, security, and deployment patterns. Incorporates the 2025 open-source community evolution and cloud-native reinterpretations of each factor.
tools
Converts user-facing documentation (how-to guides, tutorials, API references, examples) in any format — Markdown, PDF, DOCX, PPTX, XLSX, AsciiDoc, RST, HTML, Jupyter notebooks, man pages, TOML/YAML/JSON configs, and plain text — into Claude Code skill directories with SKILL.md plus thematically grouped references/*.md files. Use when given a docs directory or mixed-format documentation to transform into an AI skill. Uses MCP file-reader server for binary formats.