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ceevee_get_opportunities

Get career pivot opportunities based on the CV and a selected narrative lens (3 credits). Returns 2-4 opportunities with rationale, CV signals, and market context. This is step 2 of the positioning pipeline (after ceevee_analyze_positioning). The 'lens' value should come from ceevee_analyze_positioning output (e.g. 'Technical Leader', 'Scale-up Builder'). Pass the same session_id from step 1. Next step: ceevee_confirm_lens with selected opportunities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lensYesNarrative lens from ceevee_analyze_positioning output (e.g. 'Technical Leader', 'Scale-up Builder')
session_idNoSession ID from ceevee_analyze_positioning (step 1)
cv_version_idYesCV version ID from ceevee_upload_cv or ceevee_list_versions

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=false and idempotentHint=false. The description adds critical behavioral context not in annotations: the credit cost '(3 credits)' and the return structure 'Returns 2-4 opportunities with rationale, CV signals, and market context' (compensating for lack of output schema). It does not contradict annotations.

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?

Five sentences efficiently structured: purpose+cost, return description, pipeline position, input sourcing, and next step. Every sentence carries unique information (credit cost, output format, workflow sequence, parameter provenance). No redundancy with schema or annotations.

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?

For a multi-step workflow tool without output schema, the description adequately describes returns ('2-4 opportunities with rationale...'). It explains the 3-step pipeline context, credit consumption, and sibling dependencies. Sufficient for an agent to correctly sequence this tool in the workflow.

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

Parameters4/5

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

With 100% schema coverage, baseline is 3. The description adds valuable workflow semantics: specifies 'lens' should come from ceevee_analyze_positioning output with concrete examples ('Technical Leader', 'Scale-up Builder'), and instructs to 'Pass the same session_id from step 1', clarifying the session continuity requirement beyond the schema's type 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?

Description opens with specific verb 'Get' and resource 'career pivot opportunities'. It explicitly distinguishes itself from siblings by stating 'This is step 2 of the positioning pipeline (after ceevee_analyze_positioning)' and naming the next step 'ceevee_confirm_lens', making the workflow position crystal clear.

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 workflow guidance: specifies it comes after 'ceevee_analyze_positioning', requires the same 'session_id from step 1', and that the 'lens' value should come from the previous step's output. It explicitly names the next step, giving the agent complete context for when to invoke this tool versus its siblings.

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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