Test if a regex pattern matches text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to test against | |
| flags | No | Flags: i=ignore case, m=multiline, s=dotall | |
| pattern | Yes | Regular expression pattern |
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | ||
| error | No | ||
| matches | No | ||
| pattern | Yes | ||
| match_end | No | ||
| match_start | No | ||
| matched_text | No | ||
| valid_pattern | 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?
No annotations are provided, so the description carries the full burden. It only says 'Test if a regex pattern matches text' but doesn't disclose the return type (boolean), behavior on invalid regex, or how flags affect matching. With an output schema available, the description should at least hint at the boolean result.
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, highly concise sentence. It is front-loaded with the core purpose. However, it could include a bit more detail without losing conciseness, such as 'Returns true/false.'
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?
Given the simplicity of the tool and the availability of an output schema (context signals indicate it exists), the description is adequate but not thorough. It lacks mention of edge cases (e.g., empty pattern) or the boolean nature of the result. For a regex tool, some additional context would be helpful.
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 100%, so the schema already documents each parameter's meaning. The description adds no additional semantic context beyond the schema, meeting the baseline of 3.
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 tool's function: testing if a regex pattern matches text. The verb 'test' and nouns 'regex pattern' and 'text' are specific. It distinguishes from sibling tools like 'find_all_matches' (which returns matches) and 'regex_replace' (which substitutes patterns).
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 on when to use this tool versus alternatives such as 'validate_pattern' (for validating regex syntax) or 'find_all_matches' (for extracting matches). Missing information about prerequisites or best use cases.
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.
Many tools have overlapping purposes, such as multiple random generators (random_integer, random_number), duplicate hashing functions (hash_md5, md5_checksum), and near-identical tools (compare, compare_2, compare_decimals). The sheer number of tools and lack of clear boundaries make it difficult for an agent to differentiate.
Naming is highly inconsistent. There are duplicate tools with different names (camel_case vs to_camel_case, slug vs slugify), arbitrary suffixes like '_2', and mixing of patterns (e.g., generate_password vs password_entropy). No clear convention is followed.
With 572 tools, the server is massively overpopulated for any coherent purpose. It includes trivial endpoints (true_endpoint, null, hello_world) and numerous duplicates, far exceeding a well-scoped utility set.
While the server covers many domains (math, strings, dates, colors, etc.), the presence of duplicate and trivial tools indicates a lack of thoughtful curation. There are gaps in basic operations (e.g., no dedicated file or network tools), and many tools are redundant.
