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 skills/automazeio/mental-model-skill/mental-modelnpx skills add automazeio/mental-model-skill --skill mental-modelgit clone --depth 1 https://github.com/automazeio/mental-model-skillWrote 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/skills/automazeio/mental-model-skill/mental-model)<a href="https://agentmods.dev/skills/automazeio/mental-model-skill/mental-model"><img src="https://agentmods.dev/badge/skills/automazeio/mental-model-skill/mental-model.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 5.1 | $0.00031 | $0.00254 |
| Opus 5 | $0.00015 | $0.00127 |
| Sonnet 5 | $0.00006 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00025 |
Grade A, and why
mental-model 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 6d 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.
What it actually says
Mental Model
When working on this codebase, first check for mental-model.md in the project root.
If it exists
Read it to understand the codebase architecture, patterns, conventions, and relationships before making changes, when exploring unfamiliar parts of the code, or debugging failed tests or unexpected behavior.
Update it whenever you discover something new — from running tests, hitting unexpected behavior, or exploring unfamiliar parts of the code.
If it doesn't exist
Ask the user if they'd like you to create one. If confirmed:
Create a new file named mental-model.md at the repo root, that builds and maintains a full mental model of the codebase.
Scan the entire codebase and document how the system works end-to-end (architecture, key modules, data flow, relationships, testing approach, Docker/setup, etc).
Treat this as a living document. Update it whenever you learn something new from running tests or hitting unexpected behavior.
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.
- 6d ago First seen · 28 lines · 31 tokens per session scan A 9279b965ef8d
mental-model is a skill published in the GitHub repository automazeio/mental-model-skill (5 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 254 once invoked, about $0.0002 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.
Other skills, from other repositories
agent-expert-creation
Create specialized agent experts with pre-loaded domain knowledge using the Act-Learn-Reuse pattern. Use when building domain-specific agents that maintain mental models via expertise files and self-improve prompts.
agent-assistant
Agent assistance skill that provides stuck detection, memory management, and session learning capabilities for AI agents Trigger terms: agent stuck, loop detected, session memory, agent learning, condense memory, stuck detection, agent memory, session learnings, extraction Use when: User reports agent is stuck…
ac-knowledge-graph
Manage knowledge graph for autonomous coding. Use when storing relationships, querying connected knowledge, building project understanding, or maintaining semantic memory.
ac-memory-manager
Manage persistent memory for autonomous coding. Use when storing/retrieving knowledge, managing Graphiti integration, persisting learnings, or accessing episodic memory.
immune
Hybrid adaptive memory: Cheatsheet (positive patterns pre-generation) and Immune (negative patterns post-generation) with Hot/Cold tiered auto-learning. Triggers on: "scan for errors", "immune scan", "check output quality", "antibody scan". NOT for PR review (use pr-review) or repo audits (use repo-sentinel).
usage-audit
Audit a Claude Code setup for token waste and context bloat. Checks MCP servers, CLAUDE.md, skills, and settings against bloat filters. Triggers on: "audit my context", "usage audit", "token audit", "context bloat". NOT for codebase audits.