Offer the Journeyman's read on why a capability exists.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Capability name. | |
| npub | No | ||
| dpop_token | No | ||
| inferred_why | Yes | The Journeyman's best explanation of why this capability exists. |
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?
With no annotations, the description bears full responsibility for behavioral disclosure. It only says 'Offer...read,' implying a read operation, but does not mention side effects, auth requirements, or error handling. Important behavioral traits are missing.
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 concise sentence, which is efficient and front-loaded. However, it sacrifices informativeness for brevity, earning a 4 rather than 5.
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 tool with 4 parameters, no output schema, and no annotations, the description is minimal. It does not explain return values, prerequisites, or behavior when inputs are invalid, leaving significant gaps for agent understanding.
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?
Schema description coverage is 50%, with required parameters having minimal descriptions. The tool description adds no extra meaning beyond the schema, and optional parameters (npub, dpop_token) are undocumented. Given the gap, the description fails to compensate.
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 it 'Offer[s] the Journeyman's read on why a capability exists,' which gives a specific verb and resource but uses the unexplained term 'Journeyman.' It does not differentiate from sibling tools like 'cypher_authorize_capability_why' or 'cypher_explain_capability,' making the purpose somewhat vague.
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?
No guidance is provided on when to use this tool versus alternatives or what prerequisites are needed. The description lacks explicit context or exclusion criteria, leaving the agent without decision support.
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.
The set is heavily clustered: audit_why_exists, explain_capability, suggest_capability_why, and authorize_capability_why all answer the same basic 'why does this capability exist?' question and differ mainly in provenance/authority. Many status and provenance tools (adoption_status, session_status, service_status, issue_provenance, pr_provenance, symbol_provenance, service_provenance) also blur together without close reading.
The overwhelming majority of tools follow a predictable cypher_verb_noun pattern in snake_case, which provides strong naming consistency across a very large surface. Minor deviations such as cypher_oracle_about, cypher_oracle_how_to_join, cypher_which_service_handles, and cypher_what_realizes_capability are noticeable but do not break the overall pattern.
112 tools is an extreme count for a single MCP server, regardless of how well the clusters are named; it heavily burdens tool selection, context, and agent discovery. The set spans unrelated domains including payments, coupons, credentials, provenance, issues, patents, queries, pricing, and NOS transformations, which should be split into separate focused servers.
Many domain clusters have strong lifeycle coverage: COUPs have mint/list/update/delete/redeem, credentials have courier delivery/box status/update/delete/forget, and the named-query catalog has full CRUD plus published-tool management. Minor gaps exist—e.g., no generic list_services, no delete for capabilities, and no close/resolve action for issues—but most flows have no outright dead end.