Calculate compound interest.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual interest rate (as percentage, e.g., 5 for 5%) | |
| time | Yes | Time in years | |
| principal | Yes | Initial principal | |
| compounds_per_year | No | Compounding frequency per year |
| Name | Required | Description | Default |
|---|---|---|---|
| principal | Yes | ||
| time_years | Yes | ||
| final_amount | Yes | ||
| rate_percent | Yes | ||
| interest_earned | Yes | ||
| compounds_per_year | Yes | ||
| effective_annual_rate | Yes |
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 must carry the burden. It states 'calculate,' implying a read-only computation without side effects. However, it adds no details about the formula or output behavior. Since an output schema exists, the description needn't explain return values, so this is adequate but not proactive.
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 one sentence, which is concise. However, it could be slightly more informative without sacrificing conciseness, such as mentioning the formula or compounding frequency.
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 that the tool has a comprehensive schema and an output schema, the description is minimally complete. However, it lacks context about when to use this financial tool, especially among many siblings.
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 all parameters. The description adds no additional meaning beyond what the schema provides, meeting the baseline for high coverage.
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 'Calculate compound interest,' with a specific verb and resource. However, it does not differentiate from sibling tools like 'simple_interest' or 'loan_payment,' which have similar purposes. The title is null, further reducing clarity.
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. For instance, no mention that it handles compounding frequency, unlike simple_interest. The description is silent on usage context.
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.
