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.
git clone --depth 1 https://github.com/putervision/state-memory-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/rules/putervision/state-memory-mcp/agent-reasoning-mcp)<a href="https://agentmods.dev/rules/putervision/state-memory-mcp/agent-reasoning-mcp"><img src="https://agentmods.dev/badge/rules/putervision/state-memory-mcp/agent-reasoning-mcp/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/rules/putervision/state-memory-mcp/agent-reasoning-mcp"><img src="https://agentmods.dev/badge/rules/putervision/state-memory-mcp/agent-reasoning-mcp.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 | $0.00532 | $0.00532 |
| Opus 5.5 | $0.00213 | $0.00213 |
| Sonnet 5.5 | $0.00106 | $0.00106 |
| Haiku 4.5 | $0.00053 | $0.00053 |
Grade A, and why
agent-reasoning-mcp 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 20d 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 — 31 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Strategic Agent Reasoning (agent-reasoning-mcp)
This project uses agent-reasoning-mcp with project slug "state-memory-mcp" to manage goals, decompose complex tasks, evaluate situational trade-offs, and track decision rationale.
Mandatory Reasoning Workflow
- Start of planning: Call
set_goal(action: "create", title: "...")to establish high-level objectives. - Decomposition: Call
set_goal(action: "decompose", parent_id: "...", subgoals: [...])to break down into actionable steps. - Situational Trade-offs: Call
evaluate_situation(action: "snapshot", snapshot: {...})before selecting high-stakes actions. - Utility Configuration: Tune agent priorities with
set_utility_weights(action: "configure", weights: {...}). - Intention Dispatch: Create execution directives with
manage_intentions(action: "create", ...)for the runtime engine. - Reactive Replanning: If an unexpected blocker occurs, invoke
replan(action: "blocker", goal_id: "...", blocker_description: "...").
15 Core MCP Tools
set_goal: Manage goal hierarchy and task DAGs.evaluate_situation: Score and rank candidate actions from environment snapshots.replan: Adaptively reconstruct subgoals upon obstacles.assess_risk: Quantitative threat and risk calculation.query_knowledge: Search heuristics and past decision patterns.set_utility_weights: Configure utility weights (aggression, caution, greed, exploration).get_decision_trace: Explainable chain-of-thought rationale playback.manage_beliefs: Structured belief state with exponential confidence decay.manage_intentions: Wire contract directives queue for runtime execution.manage_reasoning_db: Snapshots, diagnostics, and SHA-256 Merkle audit verification.classify: Zero-LLM deterministic classification against hierarchical taxonomy (<2ms SLA).ask_noul: Fast binary (Yes/No/Abstain) heuristic gate evaluating conditions (<2ms SLA).ask_choice: Deterministic multi-alternative selection ranking candidate choices (<2ms SLA).ask_score: Heuristic utility evaluation scoring target entities on a bounded scale (<2ms SLA).gate_intention: Fast-path safety & feasibility filter checking preconditions before execution (<1ms SLA).
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.
- 20d ago Changed · +5 lines · +108 tokens per session b37b34f76989
- 1mo ago First seen · 26 lines · 424 tokens per session scan A 5db679f4e53b
agent-reasoning-mcp is a cursor rule published in the GitHub repository putervision/state-memory-mcp (48 stars, last pushed 13d ago), licensed MIT. It adds 532 tokens to every session, about $0.0021 per session on Opus 5.5. 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 2026-09-11.
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