psychology-agent: Skill for Claude Code

.claude/skills/iterate/SKILL.md

iterate is a skill for Claude Code from safety-quotient-lab/psychology-agent. It costs 21 tokens per session (1,884 once invoked), scanned A, original, Apache-2.0.

A work loop that checks for incoming activity, finds possible tasks, chooses the most important one, and carries it out. It can run broadly, focus on quick wins, go deeper, or filter work by an area.

In plain words
What is it for?
Use it to sync repository activity, discover tasks, select one, and execute it with an optional scope such as quick, deep, or a domain filter.
Why use it?
It turns several routine steps for finding and starting work into one repeatable command.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

This is safety-quotient-lab/psychology-agent's own configuration. It tells Claude Code how to work on psychology-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything psychology-agent configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 scripts/sync_project_board.py --mark-in-progress "{item title}".

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/safety-quotient-lab/psychology-agent/main/.claude/skills/iterate/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/safety-quotient-lab/psychology-agent

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.

agentmods badge for iterate

README.md
[![agentmods](https://agentmods.dev/badge/skills/safety-quotient-lab/psychology-agent/iterate/github.svg)](https://agentmods.dev/skills/safety-quotient-lab/psychology-agent/iterate)
Your own site
<a href="https://agentmods.dev/skills/safety-quotient-lab/psychology-agent/iterate"><img src="https://agentmods.dev/badge/skills/safety-quotient-lab/psychology-agent/iterate/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.

agentmods 80×15 button for iterate

Your own site · 80×15
<a href="https://agentmods.dev/skills/safety-quotient-lab/psychology-agent/iterate"><img src="https://agentmods.dev/badge/skills/safety-quotient-lab/psychology-agent/iterate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,884 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00021 $0.01884
Opus 5 $0.00010 $0.00942
Sonnet 5 $0.00004 $0.00377
Haiku 4.5 $0.00002 $0.00188

Measured 12d ago against content hash c0d640ba2289, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

iterate 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 12d 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.

.claude/skills/iterate/SKILL.md · 205 lines

How it starts

The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Iterate — Autonomous Work Discovery + Execution

Find the single most important thing to do next, then do it.

/sync      = check for inbound activity
/hunt      = discover candidates, present to user
/iterate   = sync → hunt → discriminate → execute → cycle

The user types /iterate and the next most important thing gets worked on.


Arguments

Parse $ARGUMENTS to determine scope:

Argument Behavior
(empty) Full hunt → discriminate → execute
quick Quick-wins hunt → discriminate → execute (XS/S items only)
deep Deep/extrapolate hunt → discriminate → execute
[domain-filter] Hunt filtered to that domain → discriminate → execute

Protocol

Phase 0: Sync (compressed)

Run a quick sync internally — not user-facing output, just input to the hunt.

  1. git fetch origin — new remote commits?
  2. git log HEAD..origin/main --oneline — anything landed?
  3. ls -t transport/sessions/*/from-*.json | head -5 — new inbound messages?
  4. gh pr list --repo safety-quotient-lab/psychology-agent --json number,title — open PRs?

If sync finds actionable items (new commits, unread transport messages, open PRs), they become candidates in Phase 1 alongside hunt results.

If clean, proceed silently to Phase 1.

Phase 1: Hunt (compressed)

Run /hunt internally — not as a user-facing presentation, but as input to the discriminator. Use the /hunt protocol (Sources 1-8) but compress output:

  • Read TODO.md, MEMORY.md Active Thread, lab-notebook.md Current State
  • Scan for candidates across all hunt sources
  • Cap at 5 candidates. If hunt surfaces more, pre-filter to the 5 with highest value/effort ratio before proceeding to Phase 2.

Output of Phase 1 is an internal candidate list, not user-facing. Format:

Candidate 1: [action] — Value: H/M/L, Effort: XS/S/M/L, Source: [where found]
Candidate 2: ...
...

Exit condition: If hunt finds zero candidates, report "Project is clean. No actionable work found." and stop.

Read the full file on GitHub · 205 lines

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.

  1. 12d ago First seen · 205 lines · 21 tokens per session scan A c0d640ba2289

Subscribe to this mod's changes

iterate is a skill published in the GitHub repository safety-quotient-lab/psychology-agent (20 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 1,884 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 2026-08-30.

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