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inite-ai

ideaudit-tools

Official
by inite-ai

compute_hiring_demand

Compute a 0-10 hiring demand score from priority-weighted ATS hit counts to evaluate startup talent demand.

Instructions

Compute hiring_demand_score (0-10) from priority-weighted ATS site hit counts (use registries/hiring-sources for priorities).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sitesYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden and does disclose the computation basis and external registry dependency. However, it does not describe return shape, error behavior, or edge cases such as empty site arrays, so behavioral transparency is only partially addressed.

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 entire description is one focused sentence with no filler. The core action, input, and output range are front-loaded, and the registry pointer is included efficiently.

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

Completeness3/5

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

The description covers the essential input semantics, priority source, and score range, which is adequate for a simple single-parameter compute tool. However, with no output schema and no annotations, the lack of explicit return format and edge-case behavior leaves some gaps for an autonomous agent.

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?

Schema property descriptions are absent (0% coverage), so the description must compensate. It does explain that 'sites' represent ATS hit counts weighted by priority and references the priority registry, but it stops short of defining the exact weighting/aggregation formula, leaving some parameter semantics to inference.

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 uses a specific verb ('Compute') and names the exact resource ('hiring_demand_score') along with its output range (0-10). It also identifies the input as 'priority-weighted ATS site hit counts,' which clearly separates it from the sibling compute_* tools that target different metrics.

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

Usage Guidelines3/5

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

The description implies when to use this tool: whenever a hiring-demand score must be derived from ATS hit counts. It also gives a useful pointer to the registry for priorities, but it does not explicitly state when to choose this tool over alternatives or mention any exclusions.

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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