Plumbline: OFAC SDN sanctions screening, SEC financials and company checks from public registries

Change a requirement by field

edit_requirement

Idempotent

Set fields by name ({"op":"set","values":{...}}, an empty value clears) or change the list ({"op":"add"|"update"|"remove"|"replace", ...}), exactly as given: no reading. Use it to answer the open question when the answer is a value.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "slug": "<slug>",
      "id": "<id>",
      "token": "<token>",
      "ops": "<ops>"
    },
    "name": "edit_requirement"
  }
}

Input Schema

Name	Required	Description
`id`	Yes	The requirement id from an earlier answer
`ops`	Yes
`slug`	Yes	The service, from list_propositions
`op_id`	No
`token`	Yes	Its private token (also the receipt token of the request it is sent as); keep it private
`base_revision`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

B3.3/5.0

Behavior3/5

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

Annotations already declare readOnly=false, idempotent=true, destructive=false, so the safety profile is covered. The description adds real value with 'exactly as given: no reading' (no read-modify-write merge) and 'an empty value clears', which an agent could not infer from annotations. It says nothing about base_revision conflict behavior, retries, or what a partially-applied op list means.

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?

The compact op-format examples are front-loaded and every clause carries information; there is no filler. The run-on parenthetical construction is dense to parse but not wasteful.

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?

For a six-parameter mutation tool with no output schema, the description covers the hardest part (the ops grammar) but omits the optimistic-concurrency role of base_revision and the purpose of op_id, leaving an agent to guess how to avoid clobbering a concurrent edit.

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?

Schema coverage is only 50%, and the description compensates by documenting the ops payload shape in detail: set with a values object, add/update/remove/replace for lists, and empty-value-means-clear semantics. base_revision, op_id, and the 30-item ops cap are still left entirely to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description says to 'set fields by name' or 'change the list', which is a clear mutation verb plus the two modes of operation. However, the resource (a requirement) only appears in the tool name and title, not in the description text, and it does not explicitly contrast with get_requirement, interpret_requirement, or send_requirement.

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?

'Use it to answer the open question when the answer is a value' gives one concrete triggering condition, which is genuinely helpful for choosing this over interpret_requirement. There is no guidance on when not to use it, how it relates to send_requirement or get_requirement, or what to do when the answer is not a value.

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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