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 big-emotion/agent-atelier --skill thoughtgit clone --depth 1 https://github.com/big-emotion/agent-atelierWrote 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/big-emotion/agent-atelier/thought)<a href="https://agentmods.dev/skills/big-emotion/agent-atelier/thought"><img src="https://agentmods.dev/badge/skills/big-emotion/agent-atelier/thought.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00858 |
| Opus 5 | $0.00017 | $0.00429 |
| Sonnet 5 | $0.00007 | $0.00172 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
thought 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.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Thought — Capture Surprising Insights
Capture a model answer that surprised you during an exploration conversation. The skill synthesizes the answer with its context, saves it as a granular entry, and updates the TL;DR synthesis file.
This skill is non-interrupting. After the thought is saved, resume the conversation exactly where it was — do not change topic or add commentary about the save.
Directory: ~/thoughts/ — created on first save; set the THOUGHTS_DIR environment variable to override.
When to Activate
- User triggers
/thoughtduring a conversation - The user just read something in your last answer that surprised them — something they were NOT thinking before
Steps
Step 1: Synthesize the Last Answer
Look at your most recent substantive answer in the conversation (the one just before the user triggered /thought).
Produce a synthesis with two parts:
-
Context (3-5 sentences max):
- What the exploration was about (the thread/topic)
- The specific question or angle that led to the surprising answer
-
Thought (3-8 sentences max):
- The synthesized insight from the model's answer
- Focus on what was surprising or non-obvious — not a generic summary
- Write in a way that will make sense when re-read weeks later without the full conversation
Step 2: Present for Confirmation
Show the synthesis to the user in this format:
**Context:** [context text]
**Thought:** [thought text]
**Suggested subject:** [1-2 word subject tag, or "none"]
Then ask: "Save this? You can: accept, reframe (tell me what to change), or cancel. You can also change or skip the subject."
Wait for the user's response. If they ask to reframe, adjust and present again. If they cancel, stop — resume conversation.
Step 3: Save the Entry
On confirmation:
- Determine the filename:
- Format:
YYYY-MM-DD-subject-slug.md(e.g.,2026-04-06-emergent-patterns.md) - If no subject:
YYYY-MM-DD-untitled.md - If filename already exists, append
-2,-3, etc.
- Format:
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 · 94 lines · 35 tokens per session scan A 76c2a1542dc4
thought is a skill published in the GitHub repository big-emotion/agent-atelier (2 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 858 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 2026-08-31.
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