deep-thinking

A written reasoning procedure for decisions that could be costly, slow, or difficult to undo.

In plain words
What is it for?
Use it before restarting services, stopping processes, running long evaluations, deleting data, or investigating intermittent failures.
Why use it?
It helps separate known facts from assumptions and consider possible effects before taking action.

Skill for Claude CodeCodexCursor

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 skills/danielsmithdevelopment/clawql/deep-thinking
Any agent
npx skills add danielsmithdevelopment/ClawQL --skill deep-thinking
Clone the repo
git clone --depth 1 https://github.com/danielsmithdevelopment/ClawQL

Made for: Claude Code, Codex, Cursor.

Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,581 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. 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 $0.00077 $0.01581
Opus 5 $0.00039 $0.00790
Sonnet 5 $0.00015 $0.00316
Haiku 4.5 $0.00008 $0.00158

Measured 2d ago against content hash dd44ac365ee6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

deep-thinking scanned grade C with 1 finding 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 2d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

- Launch a multi-minute/hour eval, train, or data wipe (`rm -rf output/…`)
.cursor/skills/deep-thinking/SKILL.md · 165 lines

How it starts

The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep thinking (chain of thought)

Externalize a written reasoning chain before irreversible or expensive actions, and a short after-action when outcomes falsify assumptions. The goal is not ceremony — it is to catch shortcut reasoning (e.g. nohup in a dying agent shell) before it burns a run.

This is thinking on the page, not a silent checklist. Prefer prose that shows why, then compress for the user-facing reply.

When to run (gates)

Invoke before acting when any of these are true:

  • Kill / restart / rebind a long-lived process (inference, MCP, Docker, tunnels)
  • Launch a multi-minute/hour eval, train, or data wipe (rm -rf output/…)
  • Choose a new start pattern over a known-good one already used this session
  • Symptoms could be process-lifecycle vs app-crash vs model-quality
  • User asks to “think hard,” “CoT,” “deep think,” or explain a decision
  • About to claim a root cause from a single datapoint

Skip for trivial edits, pure Q&A, or when the user already dictated the exact command.

How to use

  1. Write the chain (tool scratch, todo note, or a short internal block) using the template below — fill every section; mark unknowns as unknowns.
  2. Act only after the Decision section names the pick and why alternatives lost.
  3. After-action when the result surprises you or burns >~5 minutes — update assumptions and leave one sticky takeaway (optionally memory_ingest if vault tools are available).

Do not dump the full chain into every user reply unless they asked for it. User-facing: 2–6 sentences of the conclusion + the sticky takeaway. Keep the full chain in the agent trail.


Chain template (fill in order)

Copy and complete:

### CoT — <short decision title>

#### 1. Goal
What success looks like for *this* step (not the whole project).

#### 2. World state (observed, not hoped)
- Processes / ports / terminals still alive:
- What was started how (Cursor background terminal vs nohup vs systemd vs Docker):
- What dies if *this* shell exits:
- Artifacts / run ids / last known-good scores:
- Clock / duration expectations:

#### 3. Evidence so far
Bullet facts with sources (log line, exit code, healthz, pack_errors).
Separate **signal** from **interpretation**.

#### 4. Assumptions (explicit)
| # | Assumption | If false, what breaks? | How to falsify quickly? |
|---|------------|------------------------|-------------------------|
| A1 | … | … | … |

Challenge at least one assumption that feels “obvious.”

#### 5. Hypotheses (competing)
H1: …
H2: …
H3: …
What would we observe if each were true?

#### 6. Options
For each option: steps, durability, blast radius, time cost, reuse of known-good patterns.

| Option | Durability | Blast radius | Time | Notes |
|--------|------------|--------------|------|-------|
| O1 … | | | | |
| O2 … | | | | |

#### 7. Decision
Pick: Ox
Because: …
Rejected: … because …
Risk I am accepting: …
Rollback: …

#### 8. First verification
The smallest probe that proves the decision held (healthz, one smoke chat,
one doc, listener still up after parent shell ends).

#### 9. Stop conditions
Abort / rethink if: …

Read the full file on GitHub · 165 lines

Files

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.

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. 2d ago First seen · 165 lines · 77 tokens per session scan C dd44ac365ee6

Subscribe to this mod's changes

deep-thinking is a skill published in the GitHub repository danielsmithdevelopment/ClawQL (12 stars, last pushed 2d ago), licensed Apache-2.0. It adds 77 tokens to every session and 1,581 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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