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atrisorb
by atrisorb

generate_handoff

Generate an AI-powered project handoff summarizing recent activity, key changes, decisions, open questions, and next steps in markdown format.

Instructions

Generate a project handoff: an AI summary of recent activity, key changes, decisions, open questions and next steps for a project. Runs synchronously – waits for completion (tens of seconds) and returns the finished Markdown. Requires an active project (set_active_project) or an explicit project_id from list_projects. Consumes credits from the user's plan, charged once on success – prefer list_handoffs to read an existing one before generating a new one. To scope it, pass sources and/or filters (call list_filter_options first for valid values); omit both to use the project's saved scope preferences.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoPer-source advanced filters, AND-combined across dimensions. Keys MUST be source ids (an unknown source id is rejected with 400). The dimension VALUES are matched leniently – call list_filter_options first to get the real selectable values for the project rather than guessing.
sourcesNoRestrict to these source ids (omit for all connected sources). Unknown source ids are rejected with 400.
project_idNoProject id from list_projects. Overrides the active project for this call; required if no active project is set.
Behavior4/5

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

No annotations provided, so description carries full burden. Discloses synchronous execution (tens of seconds), returns Markdown, credit consumption, and requires active project. Could mention more about error cases or idempotency, but covers key 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.

Conciseness4/5

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

Description is a well-structured paragraph with core purpose upfront. Slightly lengthy due to parameter details, but every sentence adds value. Could be tightened but not excessively verbose.

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?

Given no output schema, it clearly states returns finished Markdown. References needed prerequisites (active project, list_filter_options) and sibling tools. Adequately prepares the agent for correct invocation.

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?

Schema coverage is 100% but description adds significant value: explains AND-combined filters, lenient matching, project_id overrides, and source omission behavior. Also warns about 400 errors for unknown source ids.

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 it generates a project handoff (AI summary) and specifies the verb-resource pair. It explicitly distinguishes from the sibling tool list_handoffs by advising to check for an existing one first.

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?

Provides explicit when-to-use guidance: requires an active project or project_id, advises calling list_filter_options first for valid filter values, and recommends using list_handoffs to avoid unnecessary generation.

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

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