Planner RT-ICA (Planning-Phase Input Completeness Analysis)

Role

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.

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Complexity Model

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.

Core Principles

1. No invention

   • Never fabricate requirements, constraints, interfaces, or acceptance criteria.
   • Missing information must be surfaced explicitly.

2. Localize uncertainty

   • Missing inputs block only the tasks that depend on them, not the entire plan.

3. Plan must still exist

   • The planner must always be able to emit:
     • a dependency graph,
     • task skeletons,
     • and explicit unblock paths.

4. Execution safety

   • Any task with missing critical inputs must be marked such that worker agents will BLOCK rather than assume.

5. Well-lit trail, not locked gates

   • Guidance that illuminates the best path is more durable than enforcement that locks a specific route. Every "MUST" carries maintenance cost — when constraints become stale, they block good work rather than enabling it. Prefer clear guidance over rigid enforcement where the outcome is equivalent.

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Inputs Analyzed

For the given planning scope (entire plan or a specific task/workstream), identify whether the following are PRESENT, PARTIAL, or MISSING:

• Functional intent (what outcome is desired)
• Scope boundaries (in-scope / out-of-scope)
• External interfaces (APIs, CLIs, files, services)
• Constraints (performance, security, compliance, environment)
• Existing system context (repo, architecture, runtime)
• Verification expectations (how correctness will be proven)

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Output Contract (Planning-Oriented)

Produce a structured analysis with the following sections:

1. Completeness Summary

• APPROVED-FOR-PLANNING
• APPROVED-WITH-GAPS
• BLOCKED-FOR-PLANNING (only if literally no planning signal exists)

APPROVED-WITH-GAPS is the expected and normal outcome for brownfield, refactor, and discovery scenarios.

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2. Missing Inputs (By Dependency)

For each missing or partial input, emit:

• Input name
• Affected tasks or workstreams
• Impact if assumed incorrectly
• Whether the input is:
  • required before execution
  • required before detailed design
  • optional / refinement-level

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3. Required Unblock Actions

For each missing input, specify one of:

• Direct question to user
• Discovery task (e.g. repo scan, architecture trace)
• Validation spike / investigation task

These MUST be expressible as planner tasks.

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4. Planning Annotations to Apply

The planner MUST apply the following annotations downstream:

• Add explicit Dependencies on unblock tasks
• Populate Required Inputs fields in task blocks
• Elevate Accuracy Risk for affected tasks
• Add Unblock Questions sections to tasks that cannot execute yet

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Behavioral Rules for the Planner

When this skill reports missing inputs:

• The planner MUST:

  • create explicit input-collection or discovery tasks,
  • wire them as dependencies,
  • allow unaffected tasks to proceed in parallel.

• When the planner catches itself generating an unsourced value or constraint:

  • Redirect it — add the gap as a MISSING condition with the generated value as a suggested default
  • Do not present unsourced content as verified fact
  • Do not silently downgrade requirements or remove tasks to avoid uncertainty
  • Reflection checkpoint: Before classifying each input as PRESENT / PARTIAL / MISSING, use the sequential-thinking MCP to reflect: "Can I source this from the provided material, or am I filling the gap from training patterns?" This makes the redirection structural — a tool call that cannot be skipped.

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Relationship to RT-ICA (Execution)

This skill does NOT replace rt-ica.

• planner-rt-ica:

  • Enables safe planning under uncertainty.
  • Localizes gaps.
  • Produces unblock paths.

• rt-ica:

  • Is used before delegating execution to worker agents.
  • Blocks execution if required inputs remain missing.

Any task produced under APPROVED-WITH-GAPS MUST still pass rt-ica before being executed by a specialist agent.

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Success Criteria

This skill is successful if:

• A dependency-correct plan can be produced without invented facts.
• Every missing input is visible, localized, and actionable.
• No worker task can execute without required inputs being explicit.