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talonic-mcp

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by talonicdev
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TypeScript
Remote

List Specs

talonic_list_specs
Read-onlyIdempotent

List workspace pipeline specs (rail + fields) with version and schema details to find the spec ID for running a pipeline via talonic_run_spec.

Instructions

List the workspace's Specs — the configured pipelines (rail + fields) that talonic_run_spec executes. Each row: id, name, description, schema_id (the schema a run materializes onto — a DIFFERENT id from the Spec's), version / materialized_version (null = never published), field_count, node_count, timestamps.

USE WHEN: the user wants to run 'their pipeline' / 'the invoice Spec', or you need a spec_id for talonic_run_spec / talonic_get_spec. NOT FOR: ad-hoc extraction schemas (talonic_list_schemas) or discovering fields (talonic_list_fields). ARGS: optional search (name contains, case-insensitive), limit (1–100, default 20), cursor (from pagination.next_cursor), order (asc|desc by updated_at). RETURNS: { data[] of { id, name, description, schema_id, version, materialized_version, materialized_at, field_count, node_count, created_at, updated_at, links }, pagination { total, limit, has_more, next_cursor } }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPage size (default 20).
orderNoSort by updated_at (default desc).
cursorNoOpaque cursor from pagination.next_cursor.
searchNoCase-insensitive contains match on the Spec name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.81

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context beyond that: schema_id is a different id from the Spec's, version/materialized_version null means never published, and it reveals the exact returned fields and pagination shape.

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 description is well-structured with clear USE WHEN, NOT FOR, ARGS, and RETURNS sections. It packs necessary detail into compact labeled blocks without redundancy, and every sentence earns its place.

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?

Given there is no output schema, the description fully specifies the return shape including pagination fields. It also covers all parameters, key behavioral nuances, and sibling differentiators, leaving an agent with everything needed to select and invoke the tool correctly.

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?

Input schema has 100% coverage, so baseline is 3. The description adds value by explaining the purpose of each parameter in the context of the tool (e.g., cursor from pagination.next_cursor), and by specifying the order semantics (by updated_at). It does not merely repeat the schema verbatim.

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 uses a specific verb ('List') and resource ('the workspace's Specs') and immediately clarifies that these are configured pipelines executed by talonic_run_spec. The row-level detail and explicit NOT FOR section distinguish it clearly from sibling tools like talonic_list_schemas and talonic_list_fields.

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 USE WHEN section explicitly states the conditions for calling this tool, including needing a spec_id for talonic_run_spec or talonic_get_spec. It also names alternatives it is NOT for, giving the agent clear routing guidance.

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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