UNDERSTANDING — Delete a list you own.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| context | No | Optional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It implies a destructive operation and an ownership requirement, but does not state whether deletion is permanent, what side effects occur, what happens when the list is not found or not owned, or whether confirmation is involved.
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?
The description is a single, front-loaded sentence with no filler. The leading 'UNDERSTANDING —' label adds a bit of noise but the core message is immediate and unambiguous.
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 tool this is thin: no output schema, no annotation coverage, and no mention of return values, error behavior, or ownership verification. An agent is left to guess what happens after a successful delete or on failure.
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 required 'id' parameter is undocumented in the schema and the description gives no clue about its format or how to obtain it. The optional 'context' parameter is well-described in the schema itself, but the description adds no parameter-level information to compensate for the id gap.
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?
The description states a specific verb and resource: 'Delete a list you own.' It clearly differentiates from sibling tools like delete_saved_search by naming 'list' as the target, and adds an ownership condition that scopes the operation.
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?
The intended use is implied: call this when you want to delete a list you own. However, there is no explicit guidance about when not to use it, prerequisites (e.g., must own the list), or how it relates to alternatives such as delete_saved_search or create_list.
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.
Most tools are clearly separated by artifact type or resource (find_mcp vs find_openapi vs get_provider vs get_api), but the sheer volume creates some genuinely confusable clusters: apis_io_search vs find_apis vs find_artifacts, and insights_adoption vs insights_dimensions vs find_company_insights. Several readiness-related tools (what_can_i_fix, simulate_fixes, readiness_gates) also share a conceptual boundary, though their descriptions do help.
The dominant patterns (find_*, get_*, cohort_*, compare_*) are consistent and predictable, but the set mixes in irregular names like apis_io_search, tag_group_tags, what_can_i_fix, whats_changed, and resolve. These deviations are readable but break the otherwise regular verb_noun convention.
106 tools is far beyond the typical well-scoped server and will impose a heavy selection burden on agents. The server covers a genuinely broad domain (catalog search, ratings, cohorts, agent readiness, lists, exports, feedback), so the count is defensible in scope, but it is still too many to navigate efficiently.
The surface is remarkably complete: search and browse, single-entity detail, comparisons, cohort analytics, agent-readiness assessment, saved searches, list management, feedback/correction flows, and full dataset exports are all covered. There are no obvious dead ends, and even minor operations like re-running saved searches or simulating fixes are present.
