Borrowing it
Nothing to install: this file belongs to safety-quotient-lab/psychology-agent. 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/safety-quotient-lab/psychology-agent/main/.claude/commands/capacity.mdgit clone --depth 1 https://github.com/safety-quotient-lab/psychology-agentWrote 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/safety-quotient-lab/psychology-agent/capacity)<a href="https://agentmods.dev/commands/safety-quotient-lab/psychology-agent/capacity"><img src="https://agentmods.dev/badge/commands/safety-quotient-lab/psychology-agent/capacity/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/safety-quotient-lab/psychology-agent/capacity"><img src="https://agentmods.dev/badge/commands/safety-quotient-lab/psychology-agent/capacity.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 | $0.01390 |
| Opus 5 | $0.00000 | $0.00695 |
| Sonnet 5 | $0.00000 | $0.00278 |
| Haiku 4.5 | $0.00000 | $0.00139 |
Grade C, and why
capacity scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
python3 -c "import json; d=json.load(open('${PROJECT_ROOT}/.claude/settings.json')); print('\n'.join(d.get('hooks',{}).keys()))" Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
ls "${PROJECT_ROOT}/.claude/skills/" How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/capacity — Cognitive Architecture Capacity Assessment
Assess remaining capacity across every constrained dimension of the cognitive architecture. Run at session start, when approaching a new phase of work, or when the system feels crowded.
Dimensions to Assess
1. MEMORY.md (hard constraint)
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || pwd)"
_HASH="$(echo "$PROJECT_ROOT" | tr '/' '-')"
wc -l "$HOME/.claude/projects/${_HASH}/memory/MEMORY.md"
| Threshold | Status | Action |
|---|---|---|
| < 185 | Healthy | No action needed |
| 185–199 | Pressure | Move stable content to CLAUDE.md before adding |
| 200 | At limit | Mandatory archival before any new content |
| > 200 | OVERFLOWING | System is silently truncating — fix immediately |
Report: N / 200 lines (N remaining before pressure / hard limit)
2. CLAUDE.md (advisory constraint)
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || pwd)"
wc -l "${PROJECT_ROOT}/CLAUDE.md"
Advisory limit ~200 lines. Holds stable conventions — grows slowly.
Report: N lines used (~M available before advisory limit)
3. cognitive-triggers.md (practical constraint)
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || pwd)"
wc -l "${PROJECT_ROOT}/docs/cognitive-triggers.md"
Loaded in full at T1. Practical ceiling ~900–1000 lines before context
loading becomes a meaningful tax. Above 800: flag for architectural review
(consider splitting into core + extended).
Report: N lines (~M before practical ceiling)
4. Trigger Coverage
List current triggers T1–TN and identify gaps:
T1 — Session start
T2 — Before any response
T3 — Before any recommendation
T4 — Before writing to disk
T5 — Gap check (phase boundaries)
T6 — After user pushback
T7 — After user approval
T8 — After task completion
T9 — Memory hygiene
T10 — Lesson surfaces
T11 — Cogarch self-audit
T12 — Positive pattern recognition
T13 — External content entering context
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.
- 11d ago First seen · 179 lines · 0 tokens per session scan C 76d05ea5ad35
capacity is a command published in the GitHub repository safety-quotient-lab/psychology-agent (20 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,390 tokens. A static security scan graded it C with 2 findings (reads agent configuration directories, enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.