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Identity Forge MCP

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Rank naming candidates

rank_name_candidates

Assign explicit priority ranks to naming candidates on one board in a single atomic write. Rank 1 is highest; ties allowed; only the rank field changes, leaving status, notes, and evidence untouched.

Instructions

Assign explicit user-facing priority ranks to up to 100 candidates on one naming board in a single atomic write, so every ranking applies or none does. Rank 1 is the highest priority and ties are allowed. This changes ONLY the rank field: kanban status, notes, and evidence are left untouched, so use move_name_candidates when you want to progress a candidate or record a decision. Use it to express a deliberate shortlist order for the user, not to record research. Requires the naming:write scope; it spends no AI credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rankingsYes1-100 ranking operations, applied atomically.
projectIdYesOwned naming project id from list_naming_projects.
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: atomicity ('every ranking applies or none does'), scoped side effects ('changes ONLY the rank field'), required permission ('naming:write scope'), and cost ('spends no AI credits'). This completely carries the transparency burden.

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?

Four sentences, each earning its place: purpose and constraints, rank semantics, side effects/alternative, and usage/requirements. The text is front-loaded with the core action and contains no redundancy.

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?

Despite the absence of annotations and output schema, the description covers atomicity, side-effect scope, permission, cost, and when-to-use versus alternatives. Together with the rich input schema, this forms a complete behavioral contract for the tool.

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 coverage is 100% and already provides detailed parameter descriptions (rank semantics, candidateId source, expectedUpdatedAt's optimistic concurrency). The description adds no parameter-specific meaning beyond what the schema provides, so baseline 3 applies.

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 ('Assign explicit user-facing priority ranks'), names the resource ('up to 100 candidates on one naming board'), and scopes the action clearly. It also distinguishes from the sibling 'move_name_candidates' by explicitly stating this changes only the rank field.

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 states when to use this tool ('express a deliberate shortlist order') and when not to ('not to record research'). It also directs to the alternative tool: 'use move_name_candidates when you want to progress a candidate or record a decision.'

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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