read_provenance
Return one provenance item with resolvable file URLs. slug + id required.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| slug | Yes |
humanMCP — kapoost
TDQS
C2.7/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It hints at output containing resolvable file URLs but doesn't disclose read-only behavior, error handling, or prerequisites beyond the parameter names. The description is too thin to provide meaningful behavioral transparency.
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?
Two sentences, zero fluff, and front-loaded with purpose. Ideal conciseness for a simple read operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks key context: no mention of what happens if the item isn't found, auth requirements, or any side effects. Without annotations, a simple read tool should at least clarify its read-only nature and expected output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions and the description adds no meaning to 'slug' and 'id' beyond restating their requirement. No parameter semantics are clarified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns one provenance item, using the verb 'Return' and specifying the resource. The word 'one' distinguishes it from list_provenance, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like list_provenance. It only restates required parameters, which is already in the schema, without any context for appropriate use.
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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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
B3.4/5.0
Disambiguation4/5
Most tools have clearly distinct purposes with detailed descriptions, but a few boundaries are fuzzy: leave_message vs ask_human vs leave_comment, and list_content vs list_collection could confuse an agent at first glance. Overall, the descriptions are thorough enough to disambiguate.
Naming Consistency4/5
The naming convention is predominantly snake_case with verb_noun structure (list_content, read_blob, upsert_skill). Minor deviations exist such as the mysloodsiewnia_* prefix and British spelling in synthesise_persona_patterns, but the pattern is highly recognizable and readable.
Tool Count2/5
At 41 tools, the surface area is very large for a single MCP server and exceeds the 'heavy' threshold. While each tool serves a distinct purpose, the sheer number makes the server feel bloated and harder to navigate; many tools could be grouped or pruned without losing core functionality.
Completeness4/5
The server covers a broad domain: content read/list, personas, skills management, vault CRUD (except update/delete intentionally), provenance, licensing, memory, and async question/narada workflows. Minor gaps exist like no tool to cancel a narada job or update a memory, but these are workable and the core workflows are well supported.