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 skills add quickchatai/quickchat-claude-plugin --skill improve-agentgit clone --depth 1 https://github.com/quickchatai/quickchat-claude-pluginWrote 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/quickchatai/quickchat-claude-plugin/improve-agent)<a href="https://agentmods.dev/skills/quickchatai/quickchat-claude-plugin/improve-agent"><img src="https://agentmods.dev/badge/skills/quickchatai/quickchat-claude-plugin/improve-agent/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/skills/quickchatai/quickchat-claude-plugin/improve-agent"><img src="https://agentmods.dev/badge/skills/quickchatai/quickchat-claude-plugin/improve-agent.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 | $0.00097 | $0.00954 |
| Opus 5.5 | $0.00039 | $0.00382 |
| Sonnet 5.5 | $0.00019 | $0.00191 |
| Haiku 4.5 | $0.00010 | $0.00095 |
Grade A, and why
improve-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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Improve an Agent
Read first, change second. Diagnose from real data, propose the smallest fix, and never write without explicit approval.
Before you start
- Call
list_scenariosto resolve the Agent. Config tools require EDITOR-or-above on that Agent; if the user lacks it, say so and stop. - Ask whether to PROPOSE changes only (default) or also APPLY approved ones.
Diagnose
get_assistant_settings— persona, profession, creativity, greeting, language, reply length, KB descriptions.list_knowledge_base_articles— what the Agent already knows.contenthere is a preview, not the article;get_knowledge_base_articlereturns the body.get_insightsplus alist_conversationssample read withget_conversation_detailto find where it struggled. Classify withreferences/failure-taxonomy.md.
Propose
For each recurring problem, propose the SMALLEST change that fixes it:
- Missing knowledge -> a new KB article (draft the exact text).
- Wrong tone/persona -> a specific
personality(an enum id, not a scale) or anai_commandsguideline. - Too long / short / robotic ->
reply_lengthorcreativity_level. Present proposals as a before -> after diff, then STOP for approval.
Apply (only after approval)
update_assistant_settings— pass ONLY the fields that change; effective immediately, no retrain.ai_commandsREPLACES every existing guideline, so read the current list first and send it back with the change. The list is capped at 10,000 characters in total: near the cap, merge or shorten guidelines rather than appending one more, which can only be rejected.add_knowledge_base_article— content required; embedded automatically in the background, no retrain.update_knowledge_base_article— replaces the article's WHOLE body, so read it withget_knowledge_base_articlefirst and send the full edited text.previous_title+previous_contentrestore the previous title and body, unlessprevious_content_truncatedis true.delete_knowledge_base_article— irreversible; read the article first, since the response echoes only the first 20,000 characters for recovery. It requiresexpected_titleandexpected_added_atfromlist_knowledge_base_articles(they fail the call if the article changed underneath you) plus confirm=true.set_assistant_avatar— profile picture from an image URL, a base64 data URI (png/jpg/gif/webp, max 5 MB), oruse_default=trueto reset. It permanently replaces the previous image and the legacy launcher icon, and needs a plan that allows widget customization. It returns the resultingavatar_url— there is no settings field to re-read it from.- After each other write, re-read with
get_assistant_settings/list_knowledge_base_articlesand confirm the change landed.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago Changed · +20 lines · +3 tokens per session 37f7a8a50e22
- 1mo ago First seen · 59 lines · 94 tokens per session scan A 4fb0da67e88a
improve-agent is a skill published in the GitHub repository quickchatai/quickchat-claude-plugin (1 stars, last pushed 2d ago), licensed MIT. It adds 97 tokens to every session and 954 once invoked, about $0.0004 per session on Opus 5.5. 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.
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