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163 lines
6.1 KiB
Markdown
163 lines
6.1 KiB
Markdown
---
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title: Session Insights
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description: AI-powered analysis of your agent coding sessions
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---
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AgentsView can generate AI-powered summaries and analysis of your
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coding sessions using Claude, Codex, Copilot, or Gemini. Insights
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run locally — your session data is sent to the AI agent running on
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your machine, and the generated markdown is stored in your local
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database.
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Navigate to the Insights page by clicking **More → Insights**
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in the header navigation bar. Insights, Pinned, and Trash all
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live under the **More** dropdown as of 0.21.0, which leaves
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**Sessions** and **Usage** as the top-level nav buttons.
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## Insight Types
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There are three generation modes, selected from the dropdown at
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the top of the sidebar:
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| Mode | What It Generates |
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|------|-------------------|
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| **Daily Activity** | A concise summary of what was accomplished on a single day |
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| **Date Range Activity** | A summary covering a span of days, with presets for 7 and 30 days |
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| **Agent Analysis** | A deeper analysis of patterns, effectiveness, and suggestions for improving your agent workflows. From a session page, this mode can also analyze one selected session. |
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Daily Activity and Date Range Activity both produce `daily_activity`
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type insights. Agent Analysis produces `agent_analysis` type
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insights with more detailed recommendations.
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Single-session analysis is also an `agent_analysis` insight. It is started from
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the active session header and sends `session_id` to the generation API, which
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builds the prompt from that session's messages, timing, token usage, and cost
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instead of a date-window session list. `session_id` is only accepted for
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`agent_analysis`; daily activity and canned insight modes reject it.
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## Generating an Insight
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The sidebar panel contains all the controls for generating
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insights.
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### 1. Select a Mode
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Choose **Daily Activity**, **Date Range Activity**, or
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**Agent Analysis** from the mode dropdown.
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- **Daily Activity** shows a single date picker.
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- **Date Range Activity** shows start and end date pickers with
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"Last 7 days" and "Last 30 days" preset buttons.
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- **Agent Analysis** shows a single date picker for the analysis
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target.
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### 2. Set Filters
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- **Project** — scope the insight to a specific project, or
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leave on "All Projects" for a global view.
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- **Agent** — choose which AI agent generates the insight:
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Claude, Codex, Copilot, or Gemini. Defaults to Claude.
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### 3. Add Context (Optional)
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Click **Prompt** to expand a text area where you can provide
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additional context to guide the generation. For example:
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- "Focus on test coverage improvements"
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- "Summarize the refactoring work"
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- "What patterns should I change?"
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### 4. Generate
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Click the **Generate** button (or the `+` icon). The insight
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streams in via the agent CLI running on your machine.
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While generating, a task appears in the sidebar with a spinner
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and phase indicator. You can queue multiple insights at once —
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each runs as a separate task. Use **Stop all** to cancel
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everything, or dismiss individual tasks.
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When generation completes, the insight moves to the completed
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list and is automatically selected for viewing.
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If generation fails — for example, due to an API error or
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timeout — the task shows an error status with the error
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message directly in the sidebar. This replaces the previous
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behavior where failures were silent.
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## Viewing Insights
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Select any completed insight from the sidebar list. The content
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panel displays:
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- **Type badge** — blue for daily activity, purple for agent
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analysis
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- **Date or date range** — the time period covered
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- **Metadata** — project scope, agent name, model used, and
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when the insight was created
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- **Rendered markdown** — the full insight content with
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headings, lists, code blocks, tables, and blockquotes
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## Managing Insights
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- **Delete** — click the trash icon in the insight header to
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remove it permanently.
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- **Filter by project** — changing the project dropdown filters
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the completed list to show only insights for that project
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(or global insights when set to "All Projects").
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- Insights are stored in your local SQLite database and persist
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across server restarts.
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## How It Works
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When you click Generate:
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1. AgentsView queries your session database for sessions matching
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the date range and optional project filter (up to 50 sessions).
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2. It builds a markdown prompt containing session metadata: IDs,
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projects, agents, timestamps, message counts, and first
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message previews.
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3. The prompt is sent to the selected agent CLI (`claude -p`,
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`codex exec`, `copilot -p`, `gemini`, or `kiro-cli chat
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--no-interactive`) running locally on your machine.
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4. The response streams back via Server-Sent Events, showing
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progress in the sidebar task list.
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5. The completed insight is saved to the database and displayed
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in the content panel.
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The generation has a 10-minute timeout. Your API keys and
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subscription credentials are handled by the agent CLIs
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themselves — AgentsView does not manage or store them.
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## Configuring Agent Binaries
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By default, AgentsView resolves each agent's CLI through your
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`PATH` — `claude`, `codex`, `copilot`, `gemini`, `kiro-cli`.
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If you keep multiple builds side by side, want to pin a
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known-good version, or your CLI isn't on `PATH` (a sandboxed
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install, a Homebrew keg-only formula, a custom build directory),
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add an
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`[agent.<name>]` table to `~/.agentsview/config.toml` and point
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`binary` at the executable you want used for insight generation:
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```toml
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[agent.claude]
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binary = "/opt/assets/static/agents/claude-1.7.4/bin/claude"
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[agent.gemini]
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binary = "/usr/local/bin/gemini"
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```
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Each known agent (`claude`, `codex`, `copilot`, `gemini`,
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`kiro`) has its own table; agents without a `binary` override
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fall back to `PATH` resolution. The setting only affects insight
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generation — it does not retarget session discovery, which
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always reads the on-disk session directories listed in the
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[Session Discovery](/configuration/#session-discovery) table.
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