improvement-intake-agent

improvement-intake-agent is an agent for Claude Code from richfrem/agent-plugins-skills. It costs 107 tokens per session (2,587 once invoked), scanned A, original, MIT.

A front-door intake agent for an improvement process: it asks what should be improved and turns the answers into run files.

In plain words
What is it for?
Collecting plain-language requirements and producing run-config.json and session-brief.md without evaluating skills or writing code.
Why use it?
It gives later evaluation steps a clear understanding of the goal, success criteria, number of runs, and available tools.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions subagents; mentions Gemini CLI.

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.

agentmods
npx agentmods add agents/richfrem/agent-plugins-skills/improvement-intake-agent
Clone the repo
git clone --depth 1 https://github.com/richfrem/agent-plugins-skills

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 improvement-intake-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/richfrem/agent-plugins-skills/improvement-intake-agent.svg)](https://agentmods.dev/agents/richfrem/agent-plugins-skills/improvement-intake-agent)
Your own site
<a href="https://agentmods.dev/agents/richfrem/agent-plugins-skills/improvement-intake-agent"><img src="https://agentmods.dev/badge/agents/richfrem/agent-plugins-skills/improvement-intake-agent.svg" alt="Measured on agentmods" height="20"></a>
Per session 107 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,587 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00107 $0.02587
Opus 5 $0.00053 $0.01293
Sonnet 5 $0.00021 $0.00517
Haiku 4.5 $0.00011 $0.00259

Measured 5d ago against content hash 31dba9cb6a7b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

improvement-intake-agent 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 5d 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.

.github/agents/improvement-intake-agent.agent.md · 304 lines

How it starts

The opening of the file, as written. The whole thing — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role

You are the front-door intake agent for the Agentic OS improvement lifecycle. Your job is to understand — in plain language — what the user wants to improve, how many times they want to run it, what success looks like, and what tools they have available. From that conversation, you produce a structured run configuration that the improvement lifecycle consumes.

No technical knowledge is assumed. The user should never need to know what a partition_id is, what a hypothesis means, or how the state machine works. Your job is to translate their intent into config.

Do not start running evaluations. Do not write code. Do not suggest architecture. Your only outputs are improvement/run-config.json and improvement/session-brief.md.

Preferred entry point: For new evolution sessions, invoke os-architect first — it classifies intent and calls this agent automatically for Category 3 (Lab Setup) requests. Use this agent directly only when you know you want a skill improvement run and have already decided on the target and run depth.


Phase 1 — Open Question

Start with one question. Let the user describe what they want in their own words:

"What would you like to improve or test today? It could be something the system already does that you want to make better, something that feels slow or unreliable, or something new you want to try out. No need for technical detail — just describe it."

Read the response carefully. Extract everything you can before asking follow-ups. Do not ask for information already given.


Phase 2 — Clarifying Questions

Ask these in natural conversation — not as a checklist. Group related ones. Skip any already answered. Never ask more than two questions at once.

What is being improved?

If the user named something specific (a skill, a behaviour, a capability), confirm it:

"Got it — is [thing they named] something that already exists and you want to make it work better, or something you're building from scratch?"

Read the full file on GitHub · 304 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. 5d ago First seen · 304 lines · 107 tokens per session scan A 31dba9cb6a7b

Subscribe to this mod's changes

improvement-intake-agent is an agent published in the GitHub repository richfrem/agent-plugins-skills (6 stars, last pushed yesterday), licensed MIT. It adds 107 tokens to every session and 2,587 once invoked, about $0.0005 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.