using-the-think-steplisted

Decide when to give an agent a mid-task reasoning step and how to prompt for it. Covers the no-op "think" tool that lets a model stop and reason in the middle of a tool-use chain (distinct from extended thinking, which happens before acting), the task shapes where it helps, the ones where it just adds latency, and why the gains come from system-prompt guidance rather than the tool itself. Use this whenever someone builds an agent that follows policies or makes long sequential decisions, asks whether to add a think or scratchpad tool, finds an agent skipping rules or mishandling tool output mid-task, or wants more deliberate tool use. Trigger on "think tool," "let the agent reason before acting," "agent ignores the policy," and similar. Not for general prompt engineering or one-shot chain-of-thought, and not the same as extended thinking before a turn.
pebeto/agent-stdlib · ★ 0 · AI & Automation · score 70

Install: claude install-skill pebeto/agent-stdlib

# Using the think step Source: [The "think" tool](https://www.anthropic.com/engineering/claude-think-tool). The pattern ships as MCP servers around the web; none package the judgment of *when* to use it and how to prompt it. This pack ships the tool itself under `mcp-servers/think/`; this skill is about reaching for it well. The think tool is a no-op the model can call to reason in the middle of a tool-use chain. It changes no state and returns nothing useful; its only job is to give the model a moment to lay out its reasoning before the next action. That makes it different from extended thinking, which happens once before the agent acts. The think step happens *between* actions, after the agent has seen a tool result and before it commits to what comes next. ## When it earns its place Add a think step where a wrong next action is expensive and the right one depends on what just came back: - **Reading tool output mid-chain.** The agent gets a large or messy result and has to interpret it before acting. The think step is where it does that instead of reacting. - **Policy- or compliance-heavy tasks.** The agent must check several rules before it is allowed to proceed. On the tau-bench airline domain, pairing the tool with domain guidance produced a 54% relative improvement, because the model checked the rules in the open rather than skipping them. - **Long sequential decisions where errors compound.** Each step depends on the last, so an early slip propagates. A pause to r