list_my_workflowsList durable server-owned workflow state for the authenticated TestGraph user. Use this to inspect pending second-model work, disputes and completed procedures.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context: the state is durable, server-owned, tied to the authenticated user, and includes pending, disputed, and completed procedures. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences deliver the core action and the primary use case with no filler. The description is front-loaded, clear, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, read-only list tool with one optional parameter, no output schema, and strong annotations, the description gives enough scope and use-case context for an agent to decide to call it. It slightly lacks detail on the limit parameter's effect and the exact return shape, but those are minor given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single 'limit' parameter has no schema description (0% coverage), and the description never explains what limit controls or how it affects results. With such low schema coverage, the description should compensate, but it does not; only the parameter name, default, and bounds give any hint.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('List') and a specific resource ('durable server-owned workflow state') scoped to the authenticated user. The mention of 'pending second-model work, disputes and completed procedures' also helps differentiate it from sibling list tools such as list_open_deliberations and list_my_mcp_interactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides an explicit usage instruction ('Use this to inspect...') with concrete scenarios, telling the agent when this tool is appropriate. However, it does not mention alternatives or when not to use it, stopping just short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools cluster into clear functional families — classification, location, reviews, deliberations, and system — and potentially overlapping operations are explicitly cross-referenced (e.g., enrich_subject vs correct_subject_fact, affirm vs propose reclassification). The main hazard is the resolve_subject / resolve_subject_type / resolve_subject_hierarchy trio, whose near-identical prefixes could mislead an agent at first glance despite well-written descriptions.
The surface is dominated by a consistent snake_case verb_noun pattern with stable verb families: get_*, list_*, resolve_*, set_*, save_*, create_*, register_*, and submit_*. Minor deviations — bare-verb fetch and search, and the noun-led vocabulary_index — break the pattern slightly but do not obscure it.
34 tools is heavy and above the preferred range, and the classification family alone accounts for ten tools with substantially duplicated vocabulary guidance. The count is partially earned, however, because the server genuinely spans several subsystems — reviews, subject classification, location assertions, deliberations, and governance — each with its own lifecycle.
Each subsystem has thorough lifecycle coverage: deliberations (create/claim/contribute/get/list/resolution), reviews (save/fetch/delete/list/visibility), location (assert/list/resolve), and classification (propose/affirm/reopen/relationships/aliases). Minor gaps include no way to edit review content, no direct list-all-subjects endpoint, and no retirement path for fields or aliases.