Hermes Crawler MCP Service

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: crawl, read results, login initiation, polling, cancellation, and terminal QR rendering. There is no overlap; even the three login tools have distinct actions (begin, poll, cancel).
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., crawl_url, begin_login, render_qr_terminal). The naming is predictable and the verb describes the action while the noun identifies the resource.
Tool Count5/5
With 6 tools, the server covers the core workflow of crawling with login support without being too sparse or bloated. Each tool serves a necessary step in the process, and the count feels well-scoped.
Completeness4/5
The tool set covers the essential operations: crawling, reading results, and full login lifecycle (begin, poll, cancel, plus QR rendering). Minor gaps exist, such as lacking explicit session management or crawl configuration options, but the core functionality is complete.
Average 3.4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 61 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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?
No annotations are provided, so the description carries full burden. It mentions 'releasing browser resources' but does not explain idempotency, error states (e.g., if login already completed), or side effects beyond that.
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?
The description is short (one sentence) but lacks structure. It is not front-loaded with key details, and while concise, it omits necessary information for a complete understanding.
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's side effects (cancellation, resource release) and available output schema, the description does not cover return values, error handling, or state requirements (e.g., login must be active). It is insufficient for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should clarify the parameter 'login_id'. It only implies it via context but does not explain its type, source, or usage. The agent must guess what value to provide.
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 ('cancel') and the resource ('ongoing QR code login'), and the mention of releasing browser resources differentiates it from sibling tools like begin_login, poll_login, and render_qr_terminal.
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 or not use this tool. It does not mention prerequisites (e.g., that a login must be in progress) or alternatives, leaving the agent to infer 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. States polling returns session_id upon success but omits details like polling frequency, timeout, error handling, or whether it is read-only.
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, front-loaded with purpose. Concise, though could include more specifics without becoming verbose.
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 polling tool with no annotations and limited description, key behavioral and parameter details are missing. Incomplete guidance for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%. Description does not explain the sole parameter 'login_id' (e.g., its source or format), leaving agents without guidance on how to obtain it.
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 polls login status and returns session_id for crawl_url. Verb 'poll' and resource 'login status' are specific, and it distinguishes from sibling tools like begin_login and cancel_login.
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?
Implies usage after login initiation and before crawl_url, but lacks explicit when-not-to-use or alternative scenarios. No mention of prerequisites or context.
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 carries the full burden. It implies read-only behavior by stating 'read completed results' and mentions segmented reading, but does not explicitly declare nondestructive nature, auth requirements, or rate limits. Adequate but minimal disclosure.
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?
Description is a single sentence, no fluff, and directly states the core purpose. Could be improved by front-loading the action, but overall concise and 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?
For a 3-parameter tool with no annotations, the description lacks detail on expected output, error cases, prerequisites (e.g., job must be completed), and behavior beyond segmented reading. Incomplete for reliable agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameter meanings. It mentions segmented reading, which hints at offset and max_chars, but does not directly define job_id, offset, or max_chars. Insufficient detail given the complete absence of schema 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?
Description clearly states the verb 'read' and resource 'crawl results', with additional detail about segmented reading for long documents. It distinguishes from sibling tools like crawl_url (which initiates a crawl) and login tools, making its purpose specific and unambiguous.
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?
Usage context is implied: after a crawl is completed. However, there is no explicit guidance on when to use this tool versus alternatives (e.g., crawl_url for starting, login for authentication). No 'when not to use' or prec onditions are stated.
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 provided, so description must cover behavior. It explains real-time QR capture and return of login_id, but omits expiry, idempotency, or session creation details.
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 concise sentence, front-loaded with key info. Could benefit from slight restructuring to list steps or parameters.
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?
Description covers return values and use case but does not mention output schema (likely exists) or explicitly connect to sibling tools for complete flow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% - description adds context that url is for sites needing login, but does not specify expected URL format (e.g., login page or main page).
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 initiates QR code login for sites like JD/Taobao, returns base64 QR and login_id, distinguishing it from sibling tools like poll_login and cancel_login.
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?
Usage is implied (initiate login before polling), but no explicit when-to-use or when-not-to-use compared to alternatives like poll_login.
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?
The description explicitly warns that web content is untrusted and not to execute instructions, which is a critical behavioral trait for a web crawler. No annotations are provided, so the description shoulders the burden, and it does so well here, though it could detail more behaviors like caching or loading types.
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 action, and includes a critical warning. Every sentence earns its place; no unnecessary 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?
The description provides basic purpose and a security note, but lacks details on parameters and behavior. While an output schema exists (so return values are covered), the incomplete parameter coverage and missing guidance make it merely adequate for a tool with 6 parameters and no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%: the description mentions none of the 6 parameters (url, mode, session_id, force_refresh, include_images, timeout_seconds). With low coverage, the description must compensate, but it fails to explain any parameter meanings or defaults.
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: crawling public web pages and converting to Markdown. It distinguishes itself from sibling tools (login-related, read result) by focusing on the crawling and conversion action.
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 includes a warning about untrusted content, providing some usage context. However, it does not explicitly state when to use this tool versus alternatives like read_crawl_result, nor does it specify conditions or prerequisites.
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 provided, the description carries the full burden of disclosing behavior. It explains that the tool returns an ascii_qr field that can be pasted directly, and it details the domain_mismatch conditional behavior. This adequately covers the tool's non-destructive, output-generating nature and error handling.
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 paragraph that front-loads the main purpose, then provides usage guidance and error handling. It is concise with no redundant information, earning its place with every sentence.
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 the tool's simplicity (one parameter, no nested objects, output schema exists), the description covers the main use case, output format, and the important domain_mismatch edge case. It is complete enough for an AI agent to understand when and how to use the 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?
The description does not explicitly describe the login_id parameter or its source, but the context strongly implies it comes from begin_login. Schema coverage is 0%, so the description should compensate; it partially does by referencing 'the login QR code from begin_login', but an explicit statement linking login_id to begin_login would improve clarity.
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 that the tool renders a login QR code from begin_login into a plain text terminal QR code (Unicode half-block characters) for CLI/TUI scenarios. It distinguishes itself from siblings like begin_login, which generates the QR code data, making the purpose unambiguous.
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 tells when to use the tool (after begin_login returns a QR code) and provides explicit guidance on handling domain_mismatch (do not show, recall begin_login). It also states what the caller does not need to do (download images, call system tools). However, it does not explicitly exclude sibling tools or provide criteria for choosing between them, though the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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