A diagnostic skill that builds a snapshot of an AI agent’s current workload by reading existing logs and memory files. It reports five kinds of pressure and suggests a next response.

Use it to check attention decay, token use, pending decisions, priorities, delegations, memory backlog, communication, and scheduled reviews.

It gives the agent a current view without maintaining a second state system or constantly polling files.

body-check — Skill for Claude Code by wrg32786

Install

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.

Any agent

npx skills add wrg32786/aigent-os --skill body-check

Clone the repo

git clone --depth 1 https://github.com/wrg32786/aigent-os

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/wrg32786/aigent-os/body-check/github.svg)](https://agentmods.dev/skills/wrg32786/aigent-os/body-check)

Your own site

<a href="https://agentmods.dev/skills/wrg32786/aigent-os/body-check"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/body-check/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/wrg32786/aigent-os/body-check"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/body-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 610 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00030	$0.00610
Opus 5	$0.00015	$0.00305
Sonnet 5	$0.00006	$0.00122
Haiku 4.5	$0.00003	$0.00061

Measured 8d ago against content hash 5cabd5a3c65e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

body-check 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 8d 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.

skills/body-check/SKILL.md · 59 lines

What it actually says

/body-check

Reports current body state by reading existing signals — does NOT maintain a separate state. Computed on invocation, optionally cached to memory/BODY_STATE.json for the session.

Sources read

memory/HEAT_INDEX.json → attention/decay state
memory/usage_log.md → token pressure (latest entry vs trailing 5)
memory/DECISION_LOG.md + DECISION_OUTCOMES.md → decisions due (30/60/90 day intervals)
memory/ACTIVE_PRIORITIES.md → tier-1 / mode
memory/DELEGATION_TRACKER.md → open delegations
memory/MEMORY_CANDIDATES.md → staged backlog count
memory/HESTIA_SWEEP_LOG.md → last Hestia sweep date (v0.4.4)
Comms API → unread count (only if invoked with --full)

Output schema

Matches memory/BODY_STATE.json _schema block exactly. See system/15_somatic_layer.md for field definitions and pressure thresholds.

hestia_last_sweep computation (v0.4.4)

Read memory/HESTIA_SWEEP_LOG.md. Find the most recent ### YYYY-MM-DD entry (matches ^### (\d{4}-\d{2}-\d{2}) regex). The newest matching date becomes hestia_last_sweep as ISO8601 (<date>T00:00:00Z). If no matches, hestia_last_sweep = null.

Recommended reflex logic

Priority order — first match wins:

context_pressure: critical → recommend capsule
memory_candidate_backlog > 10 → recommend digest
hestia_last_sweep is null OR more than 7 days ago → recommend sweep (v0.4.4)
decision_reviews_due > 0 → recommend (no action, surface in /open)
All low → none

When to run

On /open (auto, briefly)
Before /close (to inform the close protocol)
Anytime principal asks "how am I doing"
Before dispatching a heavy multi-agent task (catches "you're already at high context pressure")

Do NOT run on a hook polling cadence.

Changes

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.

8d ago First seen · 59 lines · 30 tokens per session scan A 5cabd5a3c65e

Subscribe to this mod's changes

body-check is a skill published in the GitHub repository wrg32786/aigent-os (18 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 610 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 2026-09-01.

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