Exact identifier match
web3_grepExact lexical match on a known identifier. Does not rank semantically.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| pattern | Yes | ||
| project | No | ||
| version | No |
web3_grepExact lexical match on a known identifier. Does not rank semantically.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| pattern | Yes | ||
| project | No | ||
| version | 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?
The readOnlyHint annotation already covers the safety profile, and the description adds useful behavioral context: matching is exact/lexical, not semantic ranking. It does not disclose pagination, limiting behavior, or what happens when no match is found, but with the annotation covering side effects, the added value is adequate.
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 short sentences, front-loaded with the core purpose and immediately followed by a differentiating clause. There is no filler, and every word contributes either to defining the match semantics or to distinguishing this tool from semantic search.
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?
With no output schema, the description should explain what the tool returns, but it does not. It also omits how project and version filter results and how limit behaves. The tool is simple and read-only, but an agent would still need more context to invoke optional parameters correctly and interpret results.
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 0%, so the description must compensate, but it only clarifies that pattern should be a known identifier. The optional parameters limit, project, and version receive no explanation of their meaning, defaults, or interaction, leaving a significant gap for correct invocation.
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: it performs an exact lexical match on a known identifier, and explicitly distinguishes itself from semantic ranking. It is clear that this is a precise lookup tool, though it does not name the underlying web3 resource being searched.
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 implies usage for known identifiers requiring exact lexical matching, and the 'does not rank semantically' clause suggests it is not for fuzzy or semantic discovery. However, it never explicitly names an alternative such as web3_search or states when not to use this tool, so the guidance remains implied rather than directive.
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.
Each tool targets a distinct retrieval need: deps for dependency closure, fetch for bodies, grep for exact matches, lookup for typed records, and search for ranked selector discovery. The descriptions even call out what each tool does not do, eliminating ambiguity.
All tools share the web3_ prefix with lowercase action-oriented names like fetch, grep, lookup, and search. The only slight inconsistency is web3_deps, which uses a noun rather than a verb, but the overall pattern remains clear and predictable.
Five tools is well-scoped for a focused web3 code context server. Each tool covers a distinct mode of retrieval without unnecessary overlap or bloat.
The set covers ranked search, exact lookup, body retrieval, dependency closure, and typed record access, forming a coherent read-only context toolkit. Minor gaps exist, such as not following calls across projects and no semantic ranking in grep or lookup, but these are explicitly stated and workable around.