Skip to main content
Glama

delimit_soul_capture

Capture session state as a soul for cross-model continuation. Saves git state, task pointers, and key decisions so the next session resumes exactly where you left off.

Instructions

Capture session state as a 'soul' for cross-model resurrection (Pro).

When to use: at session end or when context gets full, to save what you're working on so the next session in any model can pick up where you left off. When NOT to use: for general memory writes (use delimit_memory_store) or full handoff orchestration (delimit_session_handoff).

Sibling contrast: delimit_session_handoff writes a structured handoff for the next session; this writes a richer "soul" with git state and active task pointers, used by delimit_revive.

Side effects: writes a soul record via ai.session_phoenix.capture_soul. Auto-detects git state and the current model. Splits comma-string inputs into lists internally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
active_taskNoWhat you're currently working on (one line).
decisionsNoComma-separated key decisions made this session.
key_contextNoComma-separated important context for next session.
blockersNoComma-separated blockers.
next_stepsNoComma-separated next steps.
task_statusNoOne of "in_progress", "blocked", "almost_done".in_progress
tokens_usedNoEstimated tokens consumed this session.
context_fullnessNo0.0-1.0 representing context-window fullness.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses side effects ('writes a soul record via ai.session_phoenix.capture_soul'), automatic detection of git state and model, and internal splitting of comma-separated strings. No annotations provided, so the description fully covers behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured: summary sentence, when to use, when not to use, sibling contrast, side effects. Every sentence adds value; front-loaded with core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers usage, behavior, parameter details, side effects, and tier (Pro). With high schema coverage and an output schema, the description is sufficiently complete for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Adds meaning beyond schema by explaining that comma-separated parameters (decisions, key_context, etc.) are automatically split into lists, and auto-detects git state and model, enriching the parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Capture session state as a ‘soul’ for cross-model resurrection' and distinguishes it from siblings like delimit_session_handoff by highlighting richer content including git state and active task pointers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('at session end or when context gets full') and when not to use ('for general memory writes – use delimit_memory_store or full handoff orchestration – delimit_session_handoff'), with sibling contrast.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/delimit-ai/delimit-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server