An observability workspace for Claude Code

See what reaches the model.
Follow the calls behind the task.

Record Claude Code requests and responses locally. Inspect prompts, tools and context, then use timelines, snapshot comparisons and AI analysis to investigate what changed during a run. Explore it yourself, or let an agent investigate further.

  • Windows / macOS
  • English · 中文 · 日本語
  • Open source · Local records
For prompt debugging, failure investigation, subagent inspection and studying how agents work. Explore the interface

What did the model actually receive?

Expand a conversation into the request behind it.

Inspect the system prompt, history, tool definitions and call parameters alongside user input. When an answer changes or instructions conflict, start with what was actually sent.

  • Prompts and context: inspect System, Messages, tool results and reminders.
  • Call parameters: check the model, output limits and other request fields.
  • Originals and explanations: copy, format, translate or explain passages while retaining the source.
Request details (中文)

Thinking is visible only when it was returned and recorded; this is not access to all internal model reasoning.

Request details: recorded input on the left, model response on the right
Request details: recorded input on the left, model response on the right Enlarge image

Actual software UI with isolated synthetic data.

One task can involve many model calls.

Put main, subagent and auxiliary requests back into the run.

Title generation, safety checks, context compaction and retries can all happen during a task. Session lanes and turns make waits, dispatches and repeated calls easier to locate.

  • Relationships: expand turns and inspect connections between main and subagent calls.
  • Usage: compare duration, first-response timing, tokens and cache usage.
  • Failures: group similar errors, then inspect individual responses.
Timelines and relationships (中文)

Some relationships are inferred by matching rules. Check the request before treating a connection as causal.

Timeline with synthetic main and subagent lanes
Timeline with synthetic main and subagent lanes Enlarge image

Actual software UI with isolated synthetic data.

What changed between these two runs?

Save a prompt or capture as a snapshot, keeping the material available for another look.

Prompt whiteboard with two saved synthetic snapshots
Prompt whiteboard with two saved synthetic snapshots Enlarge image
Snapshot comparison showing deterministic differences and comparability notes
Snapshot comparison showing deterministic differences and comparability notes Enlarge image

Keep the material

Back up a prompt or capture from request details and organize it in the analysis workspace. Preserve the context used in your investigation.

Make differences visible

Compare prompts and context, including subtle changes in line breaks, zero-width characters and homoglyphs. Continue with a model discussion when useful.

A difference does not prove a cause. Two-prompt comparison and capture analysis are distinct workflows. Actual software UI with isolated synthetic data.

Snapshots and comparison (中文)

A little help with the long passages.

Translate or explain text blocks directly in request details, without copying them between tools.

Translate across languages

Use a text block’s translation action to read prompts, mixed-language tool results or model responses in translation.

  • Useful for long System, Messages and response passages.
  • The translation appears beside the original so you can check terminology and wording.

Ask AI to explain a passage

Start an AI explanation from a text block for help understanding complex prompts, tool content or returned text.

  • Locate the relevant content, then ask the analysis model for reading assistance.
  • Explanations remain separate from the recorded text so you can check the source.

These optional tools require an analysis model endpoint. Selected material is sent to that endpoint; check explanations against the original.

Details and reading assistance (中文)

Inspect it yourself. Let an agent go deeper.

The UI and local HTTP API use the same records. For questions spanning many requests, an agent can search and aggregate, then return to individual record IDs.

Analyze inside the app

Configure a model endpoint to translate or explain text, or continue a discussion around saved snapshots.

  • Select the material before starting the analysis.
  • Keep interpretations separate from the original content.
  • Scope, model capability and record completeness affect the result.
Snapshots and comparison (中文)

Investigate with an external agent

With the service running, ask the agent to read the built-in guide, discover available data and query it progressively.

Read CC Wire Analyzer’s /api/ai-guide first. Inspect today’s failures and slow requests, list the relevant record IDs, then check their call parameters. State what evidence is missing for any uncertain cause.

GET http://127.0.0.1:<port>/api/ai-guide

Use the port of the current instance. This is a prompt for an external agent, not a claim of continuous autonomous investigation and action.

Agent workflows (中文)

Connect Claude Code. Record the run that matters.

Download the asset for your platform. Reading saved records does not require an analysis model; configure translation and AI features when you need them.

  1. Open the app

    Choose and launch the Windows or macOS release asset.

  2. Check the upstream and start the proxy

    Follow setup, open a new Claude Code session and work as usual.

  3. Inspect the records and stop recording

    Open details or the timeline. Stop the proxy when finished and check configuration restoration.

A few things to know before starting.

Where does the data go?

The local proxy forwards requests to the configured upstream and saves records locally. Translation, AI explanations and semantic analysis send relevant material to your configured analysis endpoint. Update checks and downloads also use the network.

Can I share a recording publicly?

Authentication headers are redacted, but bodies may still contain messages, file content and secrets. Inspect the material before sharing it. Website screenshots use prepared synthetic examples.

Which tools and platforms are supported?

The current product targets Claude Code, with Windows and macOS apps and English, Chinese and Japanese UI. Other harnesses need protocol and behavior validation; research directions are not supported integrations.

Does it automatically prove a cause or guarantee success?

Error groups, timelines and model interpretations support investigation. Conclusions depend on the evidence and analysis. The manual distinguishes current behavior from future design.

Continue in the online product manual.

Illustrated steps, product requirements, API contracts and development conventions in one place. The unified manual is currently in Chinese.