Skip to main content
Glama

distill_journal_commit_upgrades

Finalizes journal entry upgrades by updating their status after subagents complete conversion to LLM-narrative.

Instructions

After dispatching subagents to upgrade mechanical journal entries to LLM-narrative, call this with the affected task slugs. Updates journal_meta.status_latest to mark the entries as upgraded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_slugsYesTask slugs whose entries were upgraded by subagents.
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly discloses the side effect: 'Updates journal_meta.status_latest to mark the entries as upgraded.' It does not mention error handling, idempotency, or reversibility, but for a simple status update the core behavior is transparent.

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?

Two sentences that are front-loaded and dense: first sentence gives the trigger, second gives the effect. No filler, no repetition of the tool name or schema.

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

Completeness4/5

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

For a single-parameter tool with no output schema, the description covers the purpose, the trigger, and the effect. It does not explain what 'mechanical journal entries' are or how to obtain the task slugs, but these are covered by sibling tools and domain context. A small gap is the lack of any mention of validation or response behavior.

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

Parameters3/5

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

The schema already provides a clear description for the only parameter (task_slugs: 'Task slugs whose entries were upgraded by subagents.'), so baseline is 3. The tool description adds minor workflow context ('affected task slugs') but no new syntax or format details beyond the schema.

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 states a specific verb and resource: 'Updates journal_meta.status_latest to mark the entries as upgraded.' It also gives workflow context ('After dispatching subagents to upgrade mechanical journal entries') that distinguishes this from sibling tools like distill_journal, which likely performs the upgrade itself.

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

Usage Guidelines4/5

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

The description clearly indicates when to use the tool: 'After dispatching subagents to upgrade... call this with the affected task slugs.' This establishes a prerequisite and sequencing. It does not explicitly name alternatives, but the 'after' clause makes the intended usage unambiguous.

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/safiyu/kontexta'

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