Point an issue at the code symbol that caused it.
| Name | Required | Description | Default |
|---|---|---|---|
| npub | No | ||
| repo_name | Yes | Repository name. | |
| dpop_token | No | ||
| symbol_fqn | Yes | Fully-qualified name of the code symbol at fault. | |
| issue_number | Yes | GitHub issue number. |
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?
No annotations are provided, and the description does not disclose behavioral traits such as side effects, permissions required, or whether links can be overwritten. For a mutation tool, this lack of transparency is insufficient.
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 with no wasted words. It is front-loaded and easy to parse, though it could benefit from slightly more detail without losing conciseness.
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?
The tool has 5 parameters, no output schema, and is a mutation operation. The description is too minimal to provide complete context; it does not explain return behavior, error conditions, or validation. More details are needed for adequate 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 60%, but the tool description only echoes the schema for two parameters (issue_number, symbol_fqn) without adding new meaning. Two parameters (npub, dpop_token) lack any description in both schema and description, providing no additional value.
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 clearly states the purpose: linking an issue to a code symbol that caused it. The verb 'point' is specific, and the resources (issue, code symbol) are identified. However, it does not differentiate from sibling tools like 'cypher_link_issue_to_capability' or 'cypher_link_pr', leaving some ambiguity.
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 description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, intended use cases, or scenarios where other sibling tools would be more appropriate.
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.