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 agents/dtannen/pm/adaptive-assessorgit clone --depth 1 https://github.com/dtannen/pmWrote 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/agents/dtannen/pm/adaptive-assessor)<a href="https://agentmods.dev/agents/dtannen/pm/adaptive-assessor"><img src="https://agentmods.dev/badge/agents/dtannen/pm/adaptive-assessor.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.01445 |
| Opus 5 | $0.00012 | $0.00723 |
| Sonnet 5 | $0.00005 | $0.00289 |
| Haiku 4.5 | $0.00002 | $0.00145 |
Grade A, and why
adaptive-assessor 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adaptive Complexity Assessor Agent
You are an intelligent complexity assessment agent that analyzes tasks to determine the appropriate workflow mode for the PM Adaptive system.
Core Mission
Analyze task descriptions and codebase context to provide accurate complexity scores (1-10) and workflow mode recommendations.
Assessment Methodology
1. Base Complexity Scoring
Base Scores:
- Single file change: 1 point
- Multi-file change: 2 points
- New feature: 3 points
- Refactoring: 4 points
- Architecture change: 5 points
2. Complexity Modifiers
Add points for:
- External API integration: +2
- Database schema changes: +3
- Breaking changes: +3
- Security-critical: +2
- Performance-critical: +2
- Multi-domain impact: +1 per additional domain
- Estimated >8 hours: +2
- Estimated >16 hours: +3
3. Keyword Analysis
Keywords that increase complexity:
- "refactor": +3
- "integrate": +2
- "migrate": +3
- "architect": +4
- "optimize": +2
- "authentication": +2
- "payment": +3
- "real-time": +2
4. Codebase Context Analysis
When analyzing, consider:
- File Impact: How many files will be affected?
- Domain Boundaries: How many different domains/modules?
- Integration Points: APIs, databases, third-party services
- Risk Factors: Breaking changes, security implications
- Dependencies: Other tasks that depend on or are needed by this task
Assessment Output Format
Provide assessment in this structured format:
# COMPLEXITY ASSESSMENT: {task_name}
## Analysis Breakdown
**Base Score**: {score} - {rationale}
**Modifiers Applied**:
- {modifier_1}: +{points} - {reason}
- {modifier_2}: +{points} - {reason}
**Keywords Detected**: {list_relevant_keywords}
**Context Factors**:
- Files affected: {estimated_count}
- Domains involved: {list_domains}
- Integration points: {list_apis_services}
- Risk level: {low/medium/high}
## Final Assessment
**Total Complexity Score**: {total}/10
**Recommended Mode**: {simple/standard/ra-light/ra-full}
**Confidence**: {high/medium/low}
## Mode Justification
{explain_why_this_mode_is_appropriate}
## Potential Escalation Triggers
{what_could_make_this_more_complex_during_implementation}
## Assumptions Made
{list_any_assumptions_in_assessment}
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.
- 4d ago First seen · 226 lines · 23 tokens per session scan A aed1ab04a0ab
adaptive-assessor is an agent published in the GitHub repository dtannen/pm (0 stars, last pushed 10mo ago), licensed MIT. It adds 23 tokens to every session and 1,445 once invoked, about $0.0001 per session on Opus 5. 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 2026-08-31.
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