agentleFS
GRIDLOCK-NYCGRIDLOCK-NYC/claude-skills/skills/plan-capacity/SKILL.md

plan-capacity

Skill0 starsChanged 7 months agoMITView on GitHub

Assess whether a task is feasible for a Claude Code agent and produce a dispatch plan. Decomposes tasks into atomic units, classifies each using Anthropic's proven decision ladder, checks delegation specs, and outputs a concrete execution plan. Use when user says 'can an agent handle this', 'is this too much for one agent', 'agent capacity', 'scope this task', 'how should I break this down', 'task scoping', 'will this thrash', 'dispatch plan', 'how many agents', or 'is this a single agent job'. Runs after a plan is produced to validate the plan's task breakdown. Do NOT use for generating the plan itself (use plan mode for that). Do NOT use for reviewing plan quality (use plan-review for that). Do NOT use for choosing between architecture approaches (use plan-directions for that).

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Every classification must trace back to a specific framework from references/decision-frameworks.md.

    line 24
  2. Distinctive:

    Read the actual codebase files a task references before assessing.

    line 26
  3. Distinctive:

    After the report, offer exactly 2 options:

    line 132
  4. Very specific:

    No plan in conversation context: If invoked without $ARGUMENTS and no plan exists, say: "No task found.

    line 141

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Agent Capacity

Assess agent feasibility for a task using Anthropic's proven decision frameworks. Produce a dispatch plan grounded in official best practices, not guesswork.

Important

  • Every classification must trace back to a specific framework from references/decision-frameworks.md. No invented heuristics.
  • Report what you find. If a task is straightforward, say so. Do not manufacture complexity to justify the skill's existence.
  • Read the actual codebase files a task references before assessing. Armchair scoping without reading code is unreliable.
  • Take your time with decomposition. A wrong dispatch plan wastes more time than a careful assessment.

Instructions

Step 1: Identify the Task

Extract the task from one of these sources:

  • $ARGUMENTS passed to the skill
  • A plan in the current conversation context
  • A pasted task description or bug list

Restate the task in one sentence so the user can confirm scope.

Step 2: Decompose into Atomic Units

Break the task into the smallest units where each unit:

  • Has a single, verifiable completion condition (test passes, grep confirms change, file exists)
  • Can be described in one sentence
  • Touches a bounded set of files

List every unit. Number them.

Step 3: Run the Enumeration Test

For the task as a whole, answer: "Can you list all subtasks before starting?"

  • YES → This is a workflow problem. Subtasks are predictable. Classify using the six workflow patterns from references/decision-frameworks.md (prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer).
  • NO → This needs agent-level autonomy. Identify which specific subtasks are unpredictable and why.

State the answer and reasoning explicitly.

Step 4: Classify Each Unit

Apply Anthropic's decision ladder to each atomic unit. Consult references/decision-frameworks.md for the full framework.

For each unit, assign exactly one classification:

ClassificationCriteriaClaude Code approach
InlineSingle prompt, 1-2 files, clear completion conditionDo it directly in main conversation
Explore subagentRead-only investigation, codebase search, file discoverysubagent_type: Explore
General subagentSelf-contained task, clear deliverable, 3-10 tool callssubagent_type: general-purpose
Sequential chainDepends on a previous unit's outputMust run after its dependency completes
Human checkpointAmbiguous requirement, judgment call, or moving-target riskPause and ask the user

Step 5: Check Delegation Specs

For every unit classified as a subagent, verify all four elements of Anthropic's delegation spec are present:

  1. Objective — Is the goal specific and unambiguous?
  2. Output format — Will the agent know what to return?
  3. Tool guidance — Does it know which files/tools to use?
  4. Task boundaries — Are scope limits explicit?

Flag any unit missing an element. A subagent dispatched without all four will "duplicate work, leave gaps, or fail to find necessary information."

Step 6: Flag Failure Patterns

Scan the full task for known failure patterns from references/decision-frameworks.md:

  • Error accumulation — Long chains where each step's error compounds
  • Over-delegation — Units that a single grep or one-file edit would handle faster than a subagent
  • Shared-context splitting — Phases that need shared context being split across subagents
  • Moving targets — Fixing unit A changes the landscape for unit B
  • Vague delegation — Units missing delegation spec elements (caught in Step 5)

Step 7: Output the Dispatch Plan

AGENT CAPACITY ASSESSMENT
═══════════════════════════════════════════
TASK: [one-line summary]
UNITS: [N total]
ENUMERABLE: [YES/NO — from Step 3]

─── DISPATCH PLAN ──────────────────────────

Phase 1 — Parallel [units that can run simultaneously]
  [U1] [INLINE] [one-line description]
  [U2] [SUBAGENT:explore] [one-line description]
  [U3] [SUBAGENT:general] [one-line description]

Phase 2 — Sequential [units depending on Phase 1]
  [U4] [INLINE] [one-line description] (depends on U1)

Phase 3 — Human checkpoint
  [U5] [HUMAN] [what needs user judgment and why]

─── FAILURE RISKS ──────────────────────────
[List any flagged patterns from Step 6, or "None identified"]

─── DELEGATION SPECS ───────────────────────
[For each subagent unit, show the 4-element spec or flag what's missing]

═══════════════════════════════════════════
TIER: [SIMPLE / COMPARISON / COMPLEX — from the three-tier scale]

Tier definitions (from Anthropic's multi-agent research system):

  • SIMPLE — 1 agent, 3-10 tool calls. Most single-file edits and lookups.
  • COMPARISON — 2-4 parallel subagents, 10-15 calls each. Module-level analysis.
  • COMPLEX — 10+ subagents with divided responsibilities. Cross-codebase work.

Step 8: Offer Execution Options

After the report, offer exactly 2 options:

  1. "Execute this dispatch plan?" — Proceed to run the phases as described.
  2. "Adjust the plan?" — User modifies scope, grouping, or classifications.

Error Handling

  1. Task is too vague to decompose: Report: "Task lacks sufficient detail. Specify: [what's missing — files, goals, success criteria]." Do not guess at decomposition.
  2. Task is a single atomic unit: Report it as SIMPLE tier, INLINE classification. Do not over-decompose. A one-line fix does not need phases.
  3. Task references files that don't exist: Flag as a potential issue — the task may be creating them, or it may be based on stale information.
  4. No plan in conversation context: If invoked without $ARGUMENTS and no plan exists, say: "No task found. Pass a task description: /agent-capacity [description] or create a plan first."
  5. All units are inline: This is valid. Report SIMPLE tier and note that no subagents are needed. Do not manufacture reasons to use subagents.

Examples

Example 1: Simple bug fix

Input: "Fix the risk.py per-market cost check — it doesn't include existing position cost"

TASK: Fix risk.py per-market cost validation to include existing position cost
UNITS: 1
ENUMERABLE: YES

Phase 1 — Inline
  [U1] [INLINE] Add existing position cost to per-market check in risk.py

FAILURE RISKS: None identified
TIER: SIMPLE

Example 2: Multi-item audit list

Input: The 12-item mm-alpha audit list (bugs + dead code + strategy gaps)

TASK: Address 12 audit findings across mm-alpha codebase
UNITS: 12
ENUMERABLE: YES

Phase 1 — Parallel (independent fixes)
  [U1] [INLINE] Fix risk.py per-market cost check (1 file, 1 line)
  [U8] [SUBAGENT:general] Remove 4 dead code items (_ensure_sdk_client, get_skew_cents, check_inventory_limits, get_expiry_bonus)
  [U5] [SUBAGENT:explore] Investigate max_quote_size usage — confirm it's truly unused

Phase 2 — Sequential
  [U2] [INLINE] Add pagination to get_fills() (depends on understanding current implementation)
  [U6] [HUMAN] Amend threshold inconsistency — which behavior is correct? (needs user judgment)
  [U7] [INLINE] Add market dequeue logic for out-of-zone markets

Phase 3 — Design required
  [U3] [HUMAN] Adverse-selection detection — needs design approval before implementation
  [U4] [HUMAN] TIME_OF_DAY_FILTERS integration — needs strategy decision

FAILURE RISKS:
- Moving target: if dead code removal (U8) changes imports, U2/U7 may need adjustment
- Over-delegation risk: U1 is a one-line fix, do not subagent it

TIER: COMPARISON

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.