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atrisorb
by atrisorb

generate_onboarding_brief

Generates a getting-started guide for new team members, highlighting key people, decisions, and pitfalls from recent project activity.

Instructions

Generate an onboarding brief: a getting-started guide for someone new to the project – key people, key decisions, pitfalls and recommended reading drawn from recent activity. Use when a new team member needs to get up to speed. Runs synchronously and returns Markdown. Consumes credits, charged once on success. Call list_filter_options before using filters.

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. Unknown ids are rejected with 400.
focus_areaNoRepository or feature area they will work on. Narrows the brief.
max_eventsNoCap on events processed (1-1000, default 400).
project_idYesProject id from list_projects to generate the brief for.
lookback_daysNoDays of history to review (1-365, default 30).
new_member_roleNoRole/focus of the person being onboarded (e.g. "backend engineer"). Tailors the brief.
Behavior4/5

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

No annotations provided, so the description carries full burden. It discloses synchronous execution, Markdown output, and credit consumption (charged once on success). It does not detail potential failure modes or rate limits, but covers essential 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?

The description is two sentences plus a filter-related instruction. Every sentence adds value: purpose, usage, behavior, prerequisite. No fluff, well front-loaded with the core action.

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 tool with 7 parameters (including nested objects) and no output schema, the description provides a solid overview. It states the output format (Markdown) and prerequisites. However, it could briefly mention that the brief is generated from recent activity (implied) and the absence of return structure guidance is a minor gap.

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 description coverage is 100%, but the description adds substantial context beyond the schema. It explains the brief's content (key people, decisions, pitfalls) and the dependency on list_filter_options for filters. This enriches understanding beyond raw parameter definitions.

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 generates an onboarding brief (a getting-started guide), with specific content like key people, decisions, pitfalls. This distinguishes it from sibling tools like generate_handoff, which is for handing off context to another person.

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?

The description explicitly says 'Use when a new team member needs to get up to speed' and instructs to 'Call list_filter_options before using filters.' This provides clear when-to-use and prerequisite guidance, leaving no ambiguity.

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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