Borrowing it
Nothing to install: this file belongs to WYRE-AI/autotask-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/WYRE-AI/autotask-mcp/main/.claude/commands/tm/analyze-complexity/analyze-complexity.mdgit clone --depth 1 https://github.com/WYRE-AI/autotask-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/wyre-ai/autotask-mcp/analyze-complexity)<a href="https://agentmods.dev/commands/wyre-ai/autotask-mcp/analyze-complexity"><img src="https://agentmods.dev/badge/commands/wyre-ai/autotask-mcp/analyze-complexity/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/wyre-ai/autotask-mcp/analyze-complexity"><img src="https://agentmods.dev/badge/commands/wyre-ai/autotask-mcp/analyze-complexity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00633 |
| Opus 5.5 | $0.00000 | $0.00253 |
| Sonnet 5.5 | $0.00000 | $0.00127 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
analyze-complexity scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
7 near-identical copies found in the catalogue:
- analyze-complexity — 100% identical, 0 lines differ
- analyze-complexity — 100% identical, 0 lines differ
- analyze-complexity — 100% identical, 12 lines differ
- analyze-complexity — 100% identical, 12 lines differ
- analyze-complexity — 100% identical, 0 lines differ
- analyze-complexity — 100% identical, 0 lines differ
- analyze-complexity — 94% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze task complexity and generate expansion recommendations.
Arguments: $ARGUMENTS
Perform deep analysis of task complexity across the project.
Complexity Analysis
Uses AI to analyze tasks and recommend which ones need breakdown.
Execution Options
task-master analyze-complexity [--research] [--threshold=5]
Analysis Parameters
--research→ Use research AI for deeper analysis--threshold=5→ Only flag tasks above complexity 5- Default: Analyze all pending tasks
Analysis Process
1. Task Evaluation
For each task, AI evaluates:
- Technical complexity
- Time requirements
- Dependency complexity
- Risk factors
- Knowledge requirements
2. Complexity Scoring
Assigns score 1-10 based on:
- Implementation difficulty
- Integration challenges
- Testing requirements
- Unknown factors
- Technical debt risk
3. Recommendations
For complex tasks:
- Suggest expansion approach
- Recommend subtask breakdown
- Identify risk areas
- Propose mitigation strategies
Smart Analysis Features
-
Pattern Recognition
- Similar task comparisons
- Historical complexity accuracy
- Team velocity consideration
- Technology stack factors
-
Contextual Factors
- Team expertise
- Available resources
- Timeline constraints
- Business criticality
-
Risk Assessment
- Technical risks
- Timeline risks
- Dependency risks
- Knowledge gaps
Output Format
Task Complexity Analysis Report
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
High Complexity Tasks (>7):
📍 #5 "Implement real-time sync" - Score: 9/10
Factors: WebSocket complexity, state management, conflict resolution
Recommendation: Expand into 5-7 subtasks
Risks: Performance, data consistency
📍 #12 "Migrate database schema" - Score: 8/10
Factors: Data migration, zero downtime, rollback strategy
Recommendation: Expand into 4-5 subtasks
Risks: Data loss, downtime
Medium Complexity Tasks (5-7):
📍 #23 "Add export functionality" - Score: 6/10
Consider expansion if timeline tight
Low Complexity Tasks (<5):
✅ 15 tasks - No expansion needed
Summary:
- Expand immediately: 2 tasks
- Consider expanding: 5 tasks
- Keep as-is: 15 tasks
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 121 lines · 0 tokens per session scan A 7eb8edfcfe21
analyze-complexity is a command published in the GitHub repository WYRE-AI/autotask-mcp (58 stars, last pushed 4d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 633 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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