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.
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- link7373/agentic-pmotheir own version, first seen Aug 9, 2026
Other versions1 project uses a version of this.
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Wrote their own version · 1
- link7373/agentic-pmo★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository21 other files it gives its agents.
- 5x5Skill
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- code-blast-radiusSkill
- code-edgesSkill
- code-preflightSkill
- code-reviewSkill
- code-securitySkill
- hail-marySkill
- organizeSkill
- plan-directionsSkill
- plan-reviewSkill
- postmortemSkill
- research-critiqueSkill
- research-searchSkill
- session-auditSkill
- session-driftSkill
- skill-builderSkill
- skill-evalSkill
- ui-ideasSkill
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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
- Very specific: line 24
Every classification must trace back to a specific framework from references/decision-frameworks.md.
- Distinctive: line 26
Read the actual codebase files a task references before assessing.
- Distinctive: line 132
After the report, offer exactly 2 options:
- Very specific: line 141
No plan in conversation context: If invoked without $ARGUMENTS and no plan exists, say: "No task found.
≈ “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.
Files
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:
$ARGUMENTSpassed 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:
| Classification | Criteria | Claude Code approach |
| Inline | Single prompt, 1-2 files, clear completion condition | Do it directly in main conversation |
| Explore subagent | Read-only investigation, codebase search, file discovery | subagent_type: Explore |
| General subagent | Self-contained task, clear deliverable, 3-10 tool calls | subagent_type: general-purpose |
| Sequential chain | Depends on a previous unit's output | Must run after its dependency completes |
| Human checkpoint | Ambiguous requirement, judgment call, or moving-target risk | Pause 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:
- Objective — Is the goal specific and unambiguous?
- Output format — Will the agent know what to return?
- Tool guidance — Does it know which files/tools to use?
- 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:
- "Execute this dispatch plan?" — Proceed to run the phases as described.
- "Adjust the plan?" — User modifies scope, grouping, or classifications.
Error Handling
- Task is too vague to decompose: Report: "Task lacks sufficient detail. Specify: [what's missing — files, goals, success criteria]." Do not guess at decomposition.
- 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.
- 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.
- No plan in conversation context: If invoked without
$ARGUMENTSand no plan exists, say: "No task found. Pass a task description:/agent-capacity [description]or create a plan first." - 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: SIMPLEExample 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: COMPARISONDoes it work?
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