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gettargetmarket: the Target Market door

File a target market statement

file_target_market

The manufacturer's agent files a target market statement for an ISIN its Legal Entity Identifier issues, under its filer identity (Authorization: Bearer ). The door checks shape, identity, LEI and subject, stores the statement at the subject's home node as the next version (immutable; a change is a new version that supersedes the last), signs it on the filer's behalf and under the node's record key, and receipts the filing with the door as writer and the filer as caller. Free.

Input Schema

NameRequiredDescriptionDefault
subjectYesThe ISIN (TEST:<ISIN-shaped> for the test namespace).
statementYesmanufacturer_name, markets, positive_target_market, negative_target_market, distribution_strategy, product_scope_statement, documentation, assessments, source (and supersedes, optional: the version it replaces). The door adds subject, manufacturer, version, filed_at, supersedes, filer, kid, sig, node, node_sig.
manufacturerYesThe manufacturer's LEI (it must be the filer identity's LEI and, for a live subject, the LEI on the subject's record).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations, the description discloses validation checks, storage at the subject's home node, immutable versioning with supersession, signing behavior, and receipt semantics. This gives the agent substantial operational context for a non-idempotent write operation.

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 purpose is front-loaded and there is no filler, but the main content is a dense single sentence with several clauses. It is concise, though the structure could be easier to parse.

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 mutation tool with no output schema, the description covers authentication, validation, storage/versioning, signing, and receipt behavior. An agent has enough information to call it correctly and understand the main side effects.

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 100%, so the schema already documents all three parameters. The description adds useful constraints, notably that the manufacturer LEI must match the filer identity and the live subject's record, and that the filer value is passed as a Bearer token.

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 states a specific verb and resource: filing a target market statement for an ISIN by the manufacturer's agent under its filer identity. This clearly distinguishes it from sibling read/verify tools such as get_target_market and verify_target_market.

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 it by specifying who files and under what identity, but it does not explicitly state when not to use it, prerequisites beyond the Bearer header, or which sibling to use for checking existing statements. Usage is inferable rather than guided.

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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