Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/asachs01/float-mcp/analyze-complexitygit clone --depth 1 https://github.com/asachs01/float-mcpWhat 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 | $0.00000 | $0.00634 |
| Opus 5 | $0.00000 | $0.00317 |
| Sonnet 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 2d 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.
This is a copy
100% identical to analyze-complexity — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 133 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.
- 2d ago First seen · 133 lines · 0 tokens per session scan A 34d40ca614df
analyze-complexity is a command published in the GitHub repository asachs01/float-mcp (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 634 tokens. A static security scan graded it A with 0 findings. It is 100% identical to analyze-complexity, differing in 12 lines, and is treated as a copy.
Other commands, from other repositories
pm-init
Initialize local .pm governance; detect Spec Kit; if absent, analyze the repo and draft a PRD for user confirmation; after confirm/skip run a technical light scan.
pm-all
Full technical governance scan; rebuild .pm/dashboard. Default does not wait on draft PRD. Use --compare-baseline only after a confirmed PRD/charter.
pm-done
Close a todo (TODO-xxx), sync completed.md, refresh overview.
pm-export
Export desensitized governance summary markdown for sharing or machine switch.
pm-outline
Generate detailed project outline and draft charter from user intent (empty/new projects).
pm-status
Show governance health, wizard next step, all open blocking/high todos, and pending review count. Primary daily entry.