Damn Vulnerable MCP Server (DVMCP)

by Kyze-Labs

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v2.0.0
Disambiguation5/5
Tools are grouped by domain prefixes (eng., fin., hr., it., mktg., support.), and each group has clearly distinct purposes. No two tools appear to overlap in functionality, making it easy for an agent to select the correct tool.
Naming Consistency5/5
All tool names follow a consistent pattern: domain prefix + verb + noun, using lowercase and underscores. Verbs are predictable (manage, query, read, run, trigger, etc.), and there is no mixing of naming conventions.
Tool Count4/5
With 28 tools spanning six domains, the count is on the higher side but still reasonable given the broad scope. Each domain has a focused set of tools, and none appear redundant.
Completeness4/5
The tool surface covers core CRUD and operational tasks across all domains. Minor gaps exist (e.g., no support ticket creation, no refund processing), but the major workflows for each domain are represented.
Average 3.5/5 across 28 of 28 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description claims the tool handles create, update, and disable but ignores the 'list' action. No disclosure of behavioral traits like permissions needed or side effects. Without annotations, the description bears full burden but is incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with actions, but second sentence is redundant with schema. Could be more concise by removing tautology.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters and no output schema, description lacks behavior details for each action (e.g., what 'list' returns). Missing coverage of all schema actions reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are documented. Description adds only that creating supports roles/permissions, which is already in schema. No additional context on formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies 'Create, update, or disable user accounts' which clearly identifies the resource and actions. However, it omits the 'list' action present in the schema, reducing clarity slightly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 siblings like 'it.execute_admin_command' or 'it.query_audit_log'. No prerequisites or alternative tools mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'query or modify' but does not disclose that the 'delete' action is destructive, nor does it discuss permissions, rate limits, or side effects. Only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently states purpose and key capabilities. It is front-loaded with the main action and resource scope. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and 3 parameters including a destructive action, the description lacks details on return format, error handling, and prerequisites. It mentions viewable fields but does not cover all actions or behaviors, leaving gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions. The description adds value by explaining what can be viewed (status, IPs, access configs) but does not clarify what each action (list, status, delete) returns or requires. Provides marginal extra meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries or modifies cloud infrastructure (EC2, RDS, S3) and mentions viewing status, IPs, and access configs. It distinguishes from sibling tools like eng.trigger_deployment, which handle deployments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. For example, it does not note that provisioning or deployment should use eng.trigger_deployment, or that read-only queries might be preferred with eng.query_repos. Missing when-not and alternative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only says 'process a payment', implying mutation, but does not disclose side effects (e.g., charging the customer), auth requirements, or reversibility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with zero wasted words. Front-loaded with verb and resource, immediately followed by supported methods. Efficiently sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Missing critical details for a payment tool: what happens on success/failure, idempotency, amount constraints relative to invoice, confirmation or response format. Not comprehensive given the tool's sensitivity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline of 3. Description restates the allowed payment methods already in the enum, adding no extra semantic value beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (process) and resource (payment for specific invoice). It distinguishes from siblings like 'fin.submit_expense' but does not differentiate from 'fin.wire_transfer', which could cause confusion as wire transfer is listed as a method here.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'fin.wire_transfer' or 'fin.submit_expense'. The description only states what it does, not when it should be chosen.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description omits behavioral details: what happens on submission (e.g., requires approval?), how listing works (filters?), side effects, or prerequisites. Barely discloses the dual-action nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, no fluff, but the second sentence largely restates the first. Efficient but could be more informative without increasing length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two distinct actions and 5 parameters, the description lacks completeness: it doesn't explain action-specific requirements, optional parameters for list vs submit, or return behavior. Without output schema, more detail is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage with clear parameter explanations. The tool description adds no further semantic value beyond the schema, hitting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool submits or lists expense reports, distinguishing it from sibling financial tools like payments or invoices. However, it uses 'expense reports' while schema fields suggest individual expense items, causing slight ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like fin.process_payment or fin.query_invoices. The description lacks context for choosing between submit and list actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It discloses generating an offer letter but omits side effects (e.g., does it send an email, create a record, require permissions?). Missing behavioral traits like authorization needs or irreversible actions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundancy. Could be improved by front-loading the core action and adding brief context, but it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no details on what is returned (e.g., document URL, text). For a sensitive HR tool, more context on workflow integration is needed. Schema only covers parameters, leaving the agent uninformed about outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 3 parameters with descriptions (e.g., 'Annual salary offer'). The description adds no extra meaning beyond mentioning 'compensation and start date', so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (generate), the resource (formal offer letter), and inputs (compensation and start date). It uniquely positions the tool among siblings like hr.review_candidate or hr.update_employee.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, no prerequisites (e.g., candidate approval), and no when-not-to-use conditions. The description is too minimal for an agent to decide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It states the tool returns details but does not disclose whether it is read-only, requires authentication, has rate limits, or any side effects. This is a significant gap for a query tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose and output. It is front-loaded and contains no redundant phrases. However, it could be slightly expanded with usage context without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter query tool with no output schema, the description provides the essential purpose and some output details. However, it omits useful context like whether the tool is read-only, pagination behavior, or authorization requirements. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters ('query' and 'language'), so the schema already explains their meaning. The tool description adds no extra parameter-level information, meeting the baseline of 3. It mentions output details (CI status, deploy keys) but that does not enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (search), resource (code repositories), and filters (by name or programming language). It differentiates from sibling tools like eng.read_source_file (which reads a specific file) and eng.manage_infrastructure (which manages infrastructure), making it unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention prerequisites, when not to use it, or any alternative tools. The agent must infer the context from the tool's name and description alone, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral transparency. It only states the operations (generate, list, revoke) and a high-level purpose. It does not disclose consequences like immediate invalidation upon revocation, rate limits, or required admin privileges, leaving a significant information gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the key actions. It is efficient without unnecessary words. However, it could be slightly more structured by separating the actions from the purpose, but it remains clear and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is minimal. It does not explain the return format (e.g., token string on generation, list of tokens on list), error conditions, or behavior of the 'scope' parameter. For a management tool, more detail is warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema; it merely restates 'action' as generate, list, or revoke. It does not clarify the 'scope' parameter's effect or provide usage examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate, list, or revoke API tokens for user accounts', which is a specific verb+resource combination. It also implies the three distinct actions, effectively distinguishing it from sibling tools like it.manage_users which handles user accounts rather than tokens.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for token management but provides no explicit guidance on when to use this tool versus alternatives (e.g., it.manage_users or it.execute_admin_command). It lacks context about prerequisites, authorization needs, or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the purpose and does not mention any behavioral traits such as read-only, destructive potential, authentication requirements, rate limits, or result handling (e.g., pagination, limit). This leaves the agent with insufficient information about side effects and constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the main purpose. It is concise with no wasted words. However, it may be too brief given the lack of behavioral transparency and parameter details, but it earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not explain the return format (e.g., snippets, full articles, IDs). It also omits details on pagination, result limits, or error handling. Given the simplicity of the tool (2 optional parameters), a bit more context on what the result looks like is expected for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; both parameters (query and category) have descriptions in the schema. The tool description adds no additional meaning beyond what the schema already provides. According to the guidelines, this warrants a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches the internal knowledge base for articles about NovaTech products, troubleshooting guides, and company policies. It uses a specific verb ('search') and resource ('knowledge base'), and distinguishes from sibling support tools like get_customer_profile, read_tickets, and reply_to_ticket.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding articles, but does not provide explicit guidance on when to use this tool versus alternatives. No when-not-to-use or alternative recommendations are given. However, the context shows no other sibling search tool, so the implied usage is adequate but could be improved.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like destructive potential, authentication needs, or error outcomes. It only mentions sudo elevation, missing critical warnings about system changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with purpose, no redundancy. Every word contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an administrative command tool, the description lacks information on return values, error handling, security risks, and synchronous behavior. With no output schema, this gap is significant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds minimal extra meaning: 'shell commands' and 'optional sudo elevation' are already implied by the schema. No new insight on timeout or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it runs administrative commands for maintenance and troubleshooting, which is a specific verb+resource. It distinguishes from sibling IT tools like get_system_config or manage_users by focusing on command execution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context ('for maintenance and troubleshooting') but does not give explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives like get_system_config for read-only tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits like side effects (e.g., whether updates are destructive), required permissions, or rate limits. The verb 'create' implies mutation, but no further transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence covering actions and key aspects. It could be more structured, but it is not verbose and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters and nested objects, the description covers core functionality but lacks details on required subfields within data, return values (no output schema), and edge cases. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds marginal value by listing data fields (name, channel, budget, target_audience, content_template) beyond the schema's minimal descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates, updates, or lists campaigns, and specifies managed details (channel, budget, target audience, email templates). It distinguishes from siblings like mktg.send_campaign_email by focusing on campaign management rather than sending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for campaign management actions but lacks explicit guidance on when to use this tool versus alternatives (e.g., mktg.send_campaign_email). No context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It indicates 'list' and 'update' actions but does not disclose whether updates are destructive, require special permissions, or how listing behaves without a platform filter. Missing details on side effects or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that efficiently conveys the core purpose without any redundant or extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description lacks details on what 'configurations' entail, the effect of updates, or the response format. For a tool with two parameters, it is incomplete in conveying the full context of usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context (NovaTech's presence on specific platforms) but does not significantly enhance understanding beyond the schema's enum descriptions. Minimal added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool lists or updates social media account configurations for NovaTech on specific platforms (Twitter, LinkedIn, Facebook), clearly distinguishing it from sibling tools like mktg.manage_campaigns or mktg.query_analytics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for managing social account configs, but does not explicitly state when to use it versus alternatives or provide exclusions. The context of sibling tools suggests differentiation, but no direct guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions 'Query... and track' but does not confirm read-only nature, rate limits, pagination, or return size. The description is insufficient for an agent to understand side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with clear first sentence and supporting examples. No unnecessary words; efficiently conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should explain return format (e.g., aggregated metrics or raw events). It does not. Also missing information on date range limitations or filtering behavior. Incomplete for a query tool with optional parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the schema already documents parameters. The description adds context by listing example event types, but this is already implied by the schema's description for event_type. No significant new meaning is added beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries user analytics and event data, listing specific metrics (page views, API calls, feature usage, user engagement). This distinguishes it from sibling marketing tools focused on campaigns, social accounts, and emails, and aligns with the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for analytics queries but provides no explicit when-to-use or when-not-to-use guidance. With many sibling tools, clearer differentiation would help, but the examples hint at appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 discloses only the basic action (sending an email) but omits side effects, authentication requirements, rate limits, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The main purpose is front-loaded, and the structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters and no output schema, the description is too brief. It does not explain return values, delivery confirmation, validation, or potential errors, leaving significant gaps for an email sending tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds minimal value beyond the schema by hinting at the relationship between template_id and custom_body, but does not provide new parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'send' and the resource 'marketing email', and distinguishes between using a campaign template or custom body. It is unique among sibling tools, as no other sibling sends emails directly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for sending marketing emails and offers two modes (template or custom). However, it lacks explicit guidance on when not to use this tool or alternatives, such as using manage_campaigns for campaign setup.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention whether execution is synchronous, requires permissions, has side effects, or how to monitor progress. This is a significant gap for a CI/CD pipeline execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The description is front-loaded with the primary action and then adds the optional override.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema, the description covers the basic use case but lacks important behavioral details (e.g., async, permissions) that an agent would need to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions. The tool description adds context for config_override ('custom build steps'), but the repo parameter receives no additional meaning. Baseline 3 with marginal added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute') and the resource ('CI/CD pipeline for a repository'), with an optional override. This distinguishes it from sibling tools like eng.manage_infrastructure or eng.trigger_deployment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
While the description clearly states what it does, it does not provide guidance on when to use this tool versus alternatives like eng.trigger_deployment, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden for behavioral disclosure. It indicates a destructive/mutating action but does not mention fees, reversibility, approval needs, or other behavioral traits typical of financial transactions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence that front-loads the purpose. No unnecessary words, and every part of the description adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and 4 parameters, the description covers required inputs but omits expected output (e.g., confirmation, reference number) and processing details. Adequate but not complete for a financial transaction tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for all parameters. The description adds 'Requires account number, routing number, and amount', which aligns with required fields, but adds little new meaning beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses 'Initiate a bank wire transfer to an external account', clearly stating the verb (initiate) and resource (wire transfer). This distinguishes it from sibling finance tools like fin.process_payment or fin.submit_expense, which handle different transaction types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies use for external wire transfers but does not specify when not to use or mention alternatives such as fin.process_payment for other payment methods. No explicit exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description must fully disclose behavioral traits. It states 'Generate' but does not clarify if this is a read-only operation, if it triggers background processing, or if it has side effects. No mention of required permissions or data mutability. The term 'Shows' implies read access, but the mutation potential is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences clearly convey the purpose and content without any unnecessary words. Front-loading the main action ('Generate a payroll report') followed by supporting details makes it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should partially fill that gap. It mentions what is shown but omits format, pagination, and any security or authorization requirements. Given the sensitivity of payroll data, permission context is missing. Complexity is moderate but not fully addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters (period and department). The description adds value by explaining that the report includes compensation, tax withholdings, and bank account details, which goes beyond the schema's minimal descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate a payroll report' (verb+resource) and specifies the report contents (compensation, tax withholdings, bank account details). It distinguishes from sibling tools like fin.export_financial_data and other HR tools such as hr.search_employees, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as when to use fin.export_financial_data for broader financial reports or hr.search_employees for individual employee details. There are no explicit use-case descriptions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It states the tool searches and filters but does not disclose behavioral traits such as pagination, ordering, rate limits, authentication needs, or whether it is read-only. As a query tool, it likely has no side effects, but this is not confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose and available filters. Every word is necessary and there is no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple query tool with three optional parameters and no output schema, the description is minimally adequate. However, it omits details about output format, result ordering, data retention, or any limitations, which would help an agent use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning the input schema already fully documents each parameter. The description merely echoes the filter dimensions without adding new semantics or usage nuances beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool searches the system audit log for security events and lists the key filter dimensions (actor, action, time range). This distinguishes it from sibling tools like it.execute_admin_command or it.manage_users, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for querying audit logs but does not provide explicit guidance on when to use it versus alternatives like it.get_system_config or other read tools. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully convey behavior. It states 'Retrieve' indicating a read-only operation, but lacks details on authentication needs, rate limits, or side effects. The absence of output schema further reduces transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and contains no redundant or wasted words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional params, no output schema), the description provides adequate context about returned fields but lacks information on error behavior, empty results, or the exact response format. More detail would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both parameters described (customer_id and email). The description adds 'Search by customer ID or email' which essentially restates the schema, adding minimal extra meaning. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'Retrieve' and identifies the resource 'customer account profiles' with details on the fields included (contact info, subscription plan, account notes). It distinguishes from sibling tools like support.read_tickets by focusing on customer profile data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving profile by customer ID or email but does not provide explicit guidance on when to use this tool over alternatives, nor does it mention prerequisites or context-specific conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behavioral traits: sends email and marks ticket resolved. However, it omits details like idempotency, failure modes, or whether the ticket must be open.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, precise, and front-loaded with the action. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple 2-parameter tool, but lacks mention of return values or any constraints on message content. The side effect of marking resolved is noted, which is good.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions already cover both parameters (ticket_id, message) with clear definitions. The descriptions add no further value beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it sends a reply to a support ticket, with specific outcomes (email sent, ticket marked resolved). This distinguishes it from sibling tools like read_tickets and search_knowledge_base.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool over alternatives or when not to use it. The description implies usage for replying to tickets, but lacks prerequisites or disclaimers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description lacks behavioral details such as permissions needed, destructiveness, reversibility, or side effects. 'Update' implies mutation, but consequences are not disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded, no redundant information. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations, and description does not mention return value, error conditions, or data validation. For a sensitive mutation tool, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value by giving concrete examples (name, role, salary, department) for the 'fields' parameter, helping agents infer expected input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool updates an employee record and lists example fields, distinguishing it from siblings like search_employees or review_candidate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage as an update tool, but no explicit guidelines on when to use vs alternatives or when not to use. No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. States read-only operation and sensitive return data, but does not disclose auth requirements, rate limits, or side effects. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff. Front-loads purpose immediately. Efficient structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity (1 optional param, no enums, no output schema), description covers purpose and return types. Missing response format or examples, but sufficient for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. Description adds general context but no additional detail beyond schema (e.g., key format, allowed values). Baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Read' and specific resource 'system configuration values'. Specifies return types (database URLs, API keys). Distinguishes from write or management siblings like 'execute_admin_command' and 'manage_api_tokens'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives, no prerequisites, permissions, or exclusions. Leaves agent to infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It fails to disclose important behavioral traits such as whether the deployment is destructive, requires permissions, is synchronous, or triggers rollbacks. Only the basic action is stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each essential. The first sentence states the core action, the second adds version detail. No redundant or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple deployment tool with 3 parameters and no output schema, the description covers the basics but omits behavioral context (e.g., side effects, async behavior). It's adequate but leaves gaps that an agent must infer or learn elsewhere.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description repeats schema's parameter explanations (e.g., version as tag/branch/SHA). No additional meaning is added beyond the structured data, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool deploys a repository to staging or production, specifying version. This is a specific verb-resource combination that distinguishes it from sibling tools like eng.run_ci_pipeline or eng.manage_infrastructure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Context is clear: use for deployment to specific environments. However, no explicit when-not-to-use or alternatives are mentioned, leaving some inference needed from sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states that data is exported as 'structured data' but does not specify the output format (e.g., JSON, CSV), pagination, rate limits, whether it's synchronous, or what happens on failure. This is insufficient for an export tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the purpose and followed by a list of report types. No unnecessary words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 clarify what 'structured data' means in terms of return format (e.g., JSON, CSV). It provides enough context for the report types and date filter but omits details about the response structure, which is critical for an export tool. Missing behavior like whether the export is immediate or asynchronous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters (report_type and date_range) with 100% coverage. The description adds value by enumerating valid values for report_type (invoices, expenses, payment_methods, payroll) and providing an example for date_range ('2026-01 to 2026-03'), which are not present in the schema as enums.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'export' and the resource 'financial reports', and lists specific report types (invoices, expenses, payment_methods, payroll). Distinguishes from sibling tools like fin.process_payment and fin.submit_expense by focusing on bulk export rather than individual transactions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Lists available report types and mentions a date range filter, providing basic usage context. However, it does not explicitly state when to use this tool over alternatives like fin.query_invoices (for querying specific invoices) or fin.submit_expense (for submitting a single expense). Lacks when-not or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that it returns ticket details including customer message body, but does not mention auth requirements, rate limits, or pagination behavior beyond the count parameter. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. First sentence defines action and resource, second adds filtering and output details. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with 3 optional parameters and no output schema, the description covers purpose, filtering, and return content. It is complete enough for the agent to understand what the tool does and how to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are already well-documented. The description adds value by confirming that status and priority are filters and mentioning the return includes message body, but does not significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads support tickets, with filtering by status and priority. It distinguishes from sibling tools like support.reply_to_ticket (write) and support.search_knowledge_base (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use (for reading tickets) and filtering options, but does not explicitly exclude other contexts or mention alternatives like searching knowledge base for solutions. It implies usage but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It indicates a read-only operation ('Retrieve') and mentions the resume. However, it lacks details on auth requirements, response format, or potential side effects, which is acceptable for a simple retrieval but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. Front-loaded with the action and resource, immediately useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 hint at return values. It mentions 'profile including their resume' but lacks specifics on structure or content. For a simple tool with one parameter, this is adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the only parameter 'candidate_id' is described inline). The description does not add additional meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves a candidate's profile and resume for review, using a specific verb and resource. It distinguishes from sibling HR tools like hr.search_employees (employees) and hr.generate_offer_letter (post-selection).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to evaluate candidates for open positions,' providing clear context for when to use it. It doesn't explicitly mention when not to use it, but the guidance is sufficient given the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It describes a read-only search operation, which is clear despite not explicitly stating it is non-destructive. Minor omission: no mention of pagination or ordering.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with front-loaded purpose. No unnecessary words, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality and return content for a simple query tool with three optional parameters. Could be slightly more complete by specifying that it returns a list, but overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add new parameter semantics beyond what the schema already provides, so no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches and filters customer invoices by status, customer name, or minimum amount, and specifies the return includes payment methods and bank transfer info. It is distinct from sibling tools like process_payment or submit_expense.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for querying invoices but does not explicitly state when to use it versus alternatives or provide any exclusion criteria. No guidance on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It mentions that include_sensitive=true includes salary, SSN, and bank details, which is important. However, it does not discuss access controls, data sensitivity risks, behavior when no results are returned, or the fact that include_sensitive defaults to true (which may be dangerous).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first states the primary purpose, the second adds essential detail about an optional parameter. No redundant information, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with three parameters and no output schema, the description is adequate. It explains the main use case and the sensitive flag. However, it does not cover pagination, ordering, error handling, or performance, which would be helpful but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, so baseline is 3. The description adds value by explaining the effect of 'include_sensitive=true' and listing what sensitive fields are included, which is not fully captured in the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'search', the resource 'employee directory', and the criteria ('by name, department, or role'). It also states the output ('employee details including contact info'). This distinguishes it from sibling tools like hr.review_candidate or hr.update_employee.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching employees but does not explicitly state when to use this tool versus other search tools or provide exclusions. It gives guidance on the include_sensitive parameter but lacks context on prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description conveys read-only behavior, but lacks details on permissions, error handling, or side effects. Adequate for a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. Front-loaded with core action. Efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should hint at return value. It does not specify what is returned (e.g., file contents). Otherwise clear for a read operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. Description adds no new information beyond what's in the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'read', resource 'source code file', and context 'from a repository'. It distinguishes from sibling tools by focusing on file reading, not infrastructure or database queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly mentions use cases (code review, debugging, understanding implementation), but does not exclude alternatives or state when not to use. Still clear enough given sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![damn-vulnerable-MCP-Server MCP server](https://glama.ai/mcp/servers/Kyze-Labs/damn-vulnerable-MCP-Server/badges/card.svg)](https://glama.ai/mcp/servers/Kyze-Labs/damn-vulnerable-MCP-Server)

Score Badge

Copy to your README.md:

[![damn-vulnerable-MCP-Server MCP server](https://glama.ai/mcp/servers/Kyze-Labs/damn-vulnerable-MCP-Server/badges/score.svg)](https://glama.ai/mcp/servers/Kyze-Labs/damn-vulnerable-MCP-Server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Kyze-Labs/damn-vulnerable-MCP-Server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server