moltalyzer

Server Quality Checklist

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

Latest release: v1.4.0
Disambiguation5/5
Each tool has a clearly distinct purpose: free samples vs paid live data vs historical for each intelligence domain, with clear differentiation between brief/full/single/batch/detail variants. No two tools appear to do the same thing; even the sample vs digest pairs are explicitly distinguished in descriptions.
Naming Consistency4/5
All tools follow a consistent 'get_<domain>_<modifier>' pattern (e.g., get_moltbook_digest, get_token_signals, get_pulse_narratives). Minor inconsistencies exist in singular/plural usage (get_tokens_latest vs get_token_signal) and a few abstract verbs (get_health, get_api_info), but overall the pattern is predictable and readable.
Tool Count4/5
23 tools is slightly over the ideal 3-15 range but justified by the multi-domain coverage (crypto, GitHub, Polymarket, Pulse, meta). Each tool serves a distinct data access need, so the count feels reasonable rather than bloated.
Completeness4/5
The toolset covers current data, samples, historical lookbacks for most domains, and batch/single retrieval for signals. Notable gaps include missing historical access for Polymarket and Pulse narratives, and no way to 'list' all available signals beyond pagination in history, but core workflows are still well covered.
Average 4/5 across 23 of 23 tools scored. Lowest: 3.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 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 status not available
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.
This repository includes a glama.json configuration file.
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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the $0.01 USDC cost via x402, which is a critical behavioral trait, and mentions the data comes from the latest daily scan, implying freshness. However, it does not mention any side effects, auth requirements, rate limits, or error behaviors. The cost is the most significant disclosure, but other operational details are missing, so a 3 is appropriate.
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 concise, consisting of two well-structured sentences. It front-loads the primary action and sorting, then lists the language filter and the returned fields, ending with the cost. Every sentence adds necessary information with zero fluff, making it easy to scan and understand quickly.
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 tool is relatively simple with only two optional parameters and no output schema. The description compensates by listing all the return fields, which is helpful. It also discloses the cost, which is important for an agent to decide whether to invoke. However, it does not mention any prerequisites like authentication for the x402 payment, or what happens if the daily scan is unavailable. Given the tool's simplicity and the absence of an output schema, the description is largely complete, but a few operational details are missing.
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 schema provides 100% description coverage for both parameters (limit with range and default, language with example and case-insensitivity). The description's mention of 'Filter by programming language' adds no new information beyond what the schema already states. It does not supplement the schema in any meaningful way, so the baseline of 3 applies.
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 retrieves top trending GitHub repos from a daily scan, sorted by stars, with optional language filtering. It lists the specific fields returned, which makes its purpose unambiguous. However, it does not explicitly differentiate itself from sibling tools like get_github_digest or get_github_history, leaving some ambiguity about which tool to use for related but distinct queries.
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 any preconditions or scenarios where this tool would be preferred over get_github_digest or get_github_history. The only hint is the 'top trending' and 'daily scan' phrasing, which implies it is for current trending data, but this is not stated explicitly. An agent would have to infer usage from the name alone.
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 provided, the description carries the full burden of behavioral disclosure. It usefully states the rate limit (1 request per 5 minutes), that it is free, and that no API key is required, which covers cost and access constraints. It also lists the output fields. However, it does not explicitly state read-only semantics (though 'Get' implies it) or mention any error conditions, such as what happens if no signal is available. The safety profile is partially covered, but not comprehensive.
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 reasonably concise, with the primary purpose front-loaded in the first sentence. It contains three sentences that each add value: purpose, output fields, and constraints. It could be slightly more streamlined (e.g., merging 'Free, rate limited...' and 'No payment or API key required' into one clause), but overall it is efficient and well-structured without redundant 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 zero-parameter tool with no output schema, the description covers the essential aspects: what it does, what it returns (list of fields), and key constraints (rate limit, free, no key). It does not describe error handling or edge cases (e.g., when no signal exists), but this is minor given the simplicity of the tool. Overall, it provides sufficient context for an agent to understand the tool's functionality and expected output.
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 tool has zero parameters, so the description has no parameter details to add. According to the rubric, a baseline of 4 is appropriate when there are no parameters. The description does not introduce any parameter-related confusion, and no additional explanation is needed.
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 verb 'Get' and the resource 'most recent Polymarket predetermined outcome signal' with a specific purpose (detecting markets where outcome is known by insiders). It also lists the returned fields, making the purpose unambiguous. However, it does not explicitly differentiate itself from sibling tools like get_polymarket_signal or get_polymarket_signals beyond the 'most recent' qualifier, which is implicit rather than explicit.
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 its siblings. It mentions rate limiting and that it is free, but does not explain selection criteria (e.g., 'use this for the latest signal, use get_polymarket_signal for a specific signal') or any conditions under which this tool should be avoided or preferred. This is a notable gap for an agent deciding between similar Polymarket tools.
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 burden. It discloses access constraints (free, rate limited to 1 per 5 minutes, no API key) and mentions that it tracks story formation across sources. However, it doesn't explicitly state it's a read-only operation or describe the response structure beyond field names, leaving some ambiguity about output shape.
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 redundancy. The first sentence front-loads the resource and key content, the second adds access details and a brief behavioral context. Every clause earns its place.
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 zero-parameter tool with no output schema and no annotations, the description covers purpose, content fields, and access constraints. It would be more complete if it noted that it returns the most recent digest (implied by 'latest'), but overall it's sufficient for an agent to call correctly.
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?
There are zero parameters, so schema coverage is trivially complete. The description compensates by explaining what the tool returns and its purpose, which is the main semantic value an agent needs. This meets the baseline of 4 for 0-param tools.
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 states a clear verb ('Get') and resource ('the full Pulse narrative intelligence digest'), and lists specific components it returns (narrativeArcs, actionableSignals, sourceMix, insights). It implies comprehensiveness with 'full' which helps distinguish from sibling tools like get_pulse_brief, but doesn't explicitly name a contrast.
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 (e.g., get_pulse_brief for summaries, get_pulse_narratives for specific arcs). Mentions rate limiting and free access but doesn't say when this tool is the right choice.
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 provided, the description bears the full burden. It usefully discloses that the call is free and requires no payment or API key, which is genuine behavioral context. However, it does not describe the response structure or detail — whether it returns a summary list, documentation links, or structured endpoint data — leaving some behavior undisclosed.
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?
Three sentences with no filler. The first sentence front-loads the core purpose and contents, the second gives the use case, and the third handles access requirements. Every sentence contributes distinct 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 zero-parameter, no-schema tool, the description covers the essential call context: what data the overview contains, when to call it, and the cost/auth profile. A minor gap is the absence of explicit output format expectation, but for a simple discovery tool this is a low-stakes omission.
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 tool has zero parameters, so the baseline is 4 per the rubric. The schema is trivially complete with no properties, and there is nothing for the description to explain. The description correctly communicates that invoking this tool requires no inputs.
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 states a clear verb and resource: 'Get Moltalyzer API overview' with specific contents (endpoints, pricing per call, changelog, rate limits). It clearly distinguishes from the data-fetching siblings by positioning this as the metadata/discovery layer of the API rather than a feed consumer, though it doesn't explicitly name a sibling it is not.
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 instruction 'Use this to discover what tools and data feeds are available' gives a clear positive use case. However, it does not explicitly state when NOT to use it or name alternatives for specific data needs. Given the many get_* siblings, explicit exclusion guidance (e.g., 'for specific datasets, use the corresponding get_* tool') would help an agent route correctly.
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?
Without annotations, the description carries the full burden. It discloses a monetary cost ($0.01 USDC via x402) and states real-time AI analysis, which implies computation. However, it does not mention idempotency, authentication requirements, rate limits, or error behavior. It adds useful operational context but is not exhaustive, warranting a 3.
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?
While a single long sentence, it is densely packed with valuable details and front-loads the core purpose. Every clause adds information (scoring, risk, metrics, chains, cost) without redundancy. It could be split for readability, but it's efficient and well-ordered, so a 4 is justified.
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 lists what the signal contains (scoring, risk, flags, liquidity/volume, social, backtest) and the chains covered, giving the agent a strong sense of the return content. It also notes the cost. It doesn't detail error cases or the exact output structure, but with no output schema and one optional param, the provided context is largely sufficient for a get-capability 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 schema covers the only parameter 'index' with a clear description ('Specific signal index number. Omit to get the latest signal.'). The description adds no additional semantics about the parameter, so with 100% schema coverage, the baseline of 3 is correct.
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 opens with a clear verb-resource pair 'Get a single token intelligence signal' and elaborates with specific content (hybrid scoring, risk, flags, metrics, social, backtest). It explicitly scopes to Ethereum, Base, and BSC, and the singular 'single' distinguishes it from sibling 'get_token_signals'. This is a specific, well-defined purpose.
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 targeting a single signal vs. the plural sibling, but does not explicitly state when to choose this over get_token_signals or other alternatives. It mentions cost as a decision factor, but lacks explicit 'use this when' or 'avoid if' guidance. The differentiation is implicit, not explicit, so a score of 3 is appropriate.
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 behavioral burden. It discloses the cost ($0.05 USDC via x402), which is critical for an agent to know before invoking the tool. It also mentions polling support. However, it does not describe side effects (it's a read operation, but that's implied), rate limits, errors, or the shape of the response. The cost disclosure adds value, but other behavioral aspects are unaddressed.
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 long with zero filler. The primary purpose is front-loaded, followed by supported features and the cost note. Every phrase earns its place—no repetition, no irrelevant details. This is an exemplar of conciseness and structure.
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 5 optional parameters, no output schema, and no annotations, the description is moderately complete. It covers the main capabilities (polling, filters, score threshold) and the cost, but it does not explain the return format or how to handle empty results or errors. An agent would understand how to invoke it but might not know what to expect in the response, which is a notable gap for a batch retrieval 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%, so every parameter is already documented in the schema. The description reiterates the chain, tier, and minScore filters and explains the tier semantics, but it does not add new meaning beyond the schema. The only slight addition is the context of polling via 'since', but that is also in the schema. Therefore, the description adds minimal value over the structured parameter definitions.
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 a specific action ('Get a batch of token intelligence signals') with a concrete resource (token intelligence signals) and a precise scope (up to 20). The verb 'Get' and the plural 'signals' immediately distinguish it from the sibling 'get_token_signal' (singular), and the mention of filtering capabilities further differentiates it from other signal tools. This is a clear, non-tautological purpose.
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 clear context on when the tool is useful—for polling via 'since' and filtering by chain, tier, and score—but it does not explicitly state when to prefer this tool over alternatives like 'get_token_signal' or 'get_polymarket_signals'. No exclusions or alternative routing are mentioned. This is adequate but leaves the agent to infer selection based on the batch nature.
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 carries the burden. It discloses return fields (symbol, score, tier, liquidity, volume, risk assessment) and rate limit. It does not mention failure modes, caching behavior, or data freshness beyond 'most recent'. Since it's a read-only 'Get', the disclosed details are adequate but not exhaustive.
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 with purpose, followed by return fields and limitations. Every sentence adds information: what it does, what it returns, and constraints. No redundant or vague phrasing.
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 no-arg read-only tool, it covers purpose, return fields, rate limit, and auth requirements. It doesn't mention error cases or what happens when rate limit is exceeded, but that is minor. It could explicitly differentiate from sibling tools like get_token_signal, but the description is clear enough for an agent to recognize its scope.
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?
Tool has zero parameters; schema is empty. Description doesn't need to explain parameters. It enriches the tool's meaning by detailing the output structure, aligning with the baseline of 4 for 0-parameter tools. The description adds value beyond the empty schema by explaining what the response contains.
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?
States a specific verb and resource: 'Get the most recent token intelligence signal' and specifies chain scope (Ethereum, Base, BSC). Lists return fields, making it clear what this tool provides. Does not explicitly name sibling alternatives but the description itself is specific and distinguishes from tools like get_token_signal by focusing on the latest cross-chain signal.
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?
Provides usage context: 'Free, rate limited to 1 request per 5 minutes. No payment or API key required.' This gives constraints but no explicit guidance on when to use this vs alternatives like get_token_signal or get_token_history. The 'most recent' hint implies a time dimension but no explicit exclusions or alternatives are mentioned.
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 full disclosure burden. It mentions the cost ($0.05 USDC via x402), which is a key behavioral aspect, and states the return type (array of daily digest objects). However, it does not explicitly state that this is a read-only operation, mention rate limits, authentication requirements, or side effects. While cost and return type add transparency, the lack of explicit safety or side-effect disclosure leaves a gap.
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 concise (two sentences) yet packs essential information: purpose, configurability, what it tracks, return type, and cost. It is front-loaded with the core action and follows with supporting details, making it easy to parse. No wasted words.
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 two optional parameters and no output schema, the description covers the purpose, return type, cost, and configurable window. It does not detail the structure of the 'digest objects' or provide error handling information, but given the context (sibling tools suggest a suite, and the agent can infer typical behavior), it is largely complete. A slightly more explicit return-structure note would push it to 5.
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 both 'days' and 'limit' already described in the input schema (ranges and defaults). The description's mention of 'configurable lookback window' aligns with 'days' but does not add new meaning beyond the schema. Since the schema is fully descriptive, the baseline of 3 applies; the description does not need to compensate.
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 ('Get'), the resource ('historical daily GitHub digests'), and the essence ('trending repo analysis over a configurable lookback window'). It also differentiates from siblings like 'get_github_digest' (likely the latest) and 'get_github_repos' (related but distinct) by emphasizing the historical and time-series nature.
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 historical analysis over a window (1-30 days) but does not explicitly state when to prefer it over alternatives. It mentions the lookback window but lacks 'use this when you need X, otherwise use Y' guidance. The presence of sibling tools (e.g., 'get_github_digest') suggests a natural context, but it's left to inference rather than spelled out.
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 behavioral burden. It discloses a cost of $0.01 USDC via x402 and describes the return content (confidence, reasoning, knowledge holder, prices, metrics), which gives the agent a good sense of side effects and output. It does not mention rate limits or reversibility, but for a read-like signal retrieval that is acceptable.
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, zero wasted words. The core purpose and return fields are front-loaded, and the cost note is appended clearly. Perfectly sized for the tool's simplicity.
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 tool with one optional parameter, no output schema, and no annotations, the description covers purpose, cost, and return contents. It is complete enough for an agent to call it correctly. Minor gaps (e.g., how to obtain a valid index) are not critical since omitting it defaults to the latest signal.
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 already describes the 'index' parameter fully ('Specific signal index number. Omit to get the latest signal.'), so schema coverage is 100%. The description adds nothing beyond what the schema provides, meeting the baseline for adequate param semantics.
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 verb 'Get', the resource 'a single Polymarket predetermined outcome signal', and defines what that means (AI-detected markets with known outcomes). It distinguishes from the plural sibling 'get_polymarket_signals' by emphasizing 'single' and 'predetermined outcome', but does not explicitly name alternatives. Strong purpose but not maximal differentiation.
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 (when you want a single specific signal vs. a list) through the word 'single', but it does not state when to prefer this tool over get_polymarket_signals or get_polymarket_latest, nor any exclusions or prerequisites. Guidance is implied, not explicit.
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?
There are no annotations, so the description carries the full burden. It discloses the cost ($0.03 USDC via x402) and the nature of the operation (historical retrieval). However, it does not explicitly state that the tool is read-only or non-destructive, nor does it mention any authentication or rate limits. Still, the 'Get' verb implies a read operation, and the cost is a key behavioral fact, so this is above the minimum but not comprehensive.
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 with no redundancy. The primary purpose and configurable window are front-loaded, followed by the cost. Every word earns its place, making it highly scannable.
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 tool with only two simple parameters, no output schema, and no nested objects, the description provides sufficient context: the resource type (Master Intelligence Digests) and the purpose (track evolution over time). It does not detail the return format, but the absence of an output schema means the description need not explain a complex structure. Overall, it covers the essentials.
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% — both parameters have full descriptions. The tool description adds no extra parameter detail beyond mentioning the lookback window, which is already covered. As such, this is a baseline 3; the description does not need to compensate.
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 ('Get historical Master Intelligence Digests'), the resource (digests), and the key differentiator (configurable lookback window). It stands out from siblings like get_intelligence_digest (presumably current) and get_intelligence_sample, so an agent can easily distinguish it.
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 communicates the intended use case ('Track how the unified intelligence picture evolves over time') and specifies a configurable lookback, which gives clear context. However, it does not explicitly name alternative tools or state when NOT to use it, though the context is clear enough for a historical query tool.
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 carry the behavioral burden. It discloses the cost ('$0.02 USDC via x402') and the return format ('array of hourly digest objects'), which are useful. However, it omits details like authentication requirements, rate limits, or error handling. Since it is a read-only 'get' operation, side effects are minimal, but the description could mention that it is non-destructive. It adds some value but not comprehensive 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 compact: three sentences delivering purpose, use case, return type, and cost. It is front-loaded with the core function, and every sentence carries information without redundancy. There is no fluff or repetition.
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 read-only history tool with only two well-documented parameters and no nested objects, the description covers the essential aspects: what it does, when to use it, what it returns, and its cost. It lacks some details like the precise structure of the digest objects (e.g., sentiment scores or topic names), but since there is no output schema, the description is expected to provide only a high-level return format. Minor gaps like error handling are not critical for this simple 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 input schema has 100% coverage with clear descriptions for both parameters (hours and limit), so the baseline is 3. The description's mention of a 'configurable lookback window' aligns with the 'hours' parameter but does not add substantive new meaning beyond paraphrasing the schema. It adds marginal value, so a 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 tool returns 'historical Moltbook community digests' with an explicit 'lookback window', and describes the content as 'hourly sentiment analysis'. The word 'historical' and the contrast with 'Moltbook community digests' differentiates it from sibling tools like get_moltbook_digest (likely current) and get_moltbook_sample. This is a specific verb+resource that stands alone.
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 gives a direct use case: 'Use this to track how community sentiment, topics, and narratives have evolved over time.' This clearly implies the tool is for historical analysis and not for current snapshots. However, it does not explicitly name sibling alternatives or state when not to use it, so it falls short of a 5 but provides clear 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 provided, the description carries the full burden of behavioral disclosure. It discloses the cost ($0.01 USDC via x402) and the output fields, but does not explicitly state that it is a read-only operation (implied by 'Get'), nor does it mention rate limits, pagination, or authentication requirements. While safe, it leaves some behavioral aspects implicit due to lack of annotations.
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 concise, two sentences long, and front-loads the core purpose ('Get all active Pulse narratives') before providing supporting details on what narratives are and the cost. Every sentence adds relevant information without redundancy or fluff.
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 has no parameters and no output schema, the description covers the key information an agent needs: what it returns (all active narratives with specific fields), the definition of a narrative, and the cost. It does not mention pagination or response format, but for a simple get-all tool, this is largely complete. The sibling detail tool is not referenced, which could be useful, but the purpose is clear enough.
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 tool has zero parameters, so parameter semantics are trivially satisfied; the baseline is 4. The description adds context about narratives themselves, which helps an agent understand the domain, but since there are no parameters to explain, it appropriately focuses on tool behavior rather than parameters.
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 states a clear verb and resource: 'Get all active Pulse narratives' with specific data fields (lifecycle stage, source count, momentum). It also defines what a narrative is (stories across 2+ sources) and lists sources, distinguishing this from the sibling get_pulse_narrative_detail tool which focuses on a single narrative.
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 context about the tool's function but does not explicitly state when to use it versus alternatives. While the name and purpose imply it is for listing narratives, there is no mention of when not to use it or when to prefer sibling tools like get_pulse_narrative_detail. Usage guidance is implied but not explicit.
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 full behavioral burden. It discloses the update frequency (hourly), rate limit, and authentication requirements, and describes the content structure (executive summary, cross-domain insights, narratives, sentiment). This exceeds basic expectations, though it does not detail error handling or output format beyond the description.
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, but it is dense and front-loaded with the specific verb and resource. It packs multiple details (sources, content, update frequency, rate limit, auth) without redundant phrasing. Slightly long but 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 zero-parameter, no-output-schema tool, the description covers all essential aspects: what it returns, how often it updates, and access constraints. An agent can call it correctly with no ambiguity. It lacks only minor details like response format or pagination, but these are not required for a digest tool.
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 tool has zero parameters, so the schema carries no burden. The description adds value by explaining what the tool returns, which is the only parameter-like context needed. Baseline 4 is appropriate for a no-parameter tool, and the description is informative.
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 retrieves the 'latest Master Intelligence Digest' and specifies that it is a cross-domain synthesis combining multiple sources (crypto sentiment, GitHub trends, Polymarket signals, token intelligence) into a unified analysis. This distinguishes it from siblings like get_github_digest or get_polymarket_latest, which focus on single domains.
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 practical usage constraints (free, rate limited to 1 request per 5 minutes, no payment or API key required) but does not explicitly state when to use this tool versus the individual domain digests. It implies it is the aggregate option, but an agent might need more explicit routing guidance given the many 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 full burden of behavioral disclosure. It fully discloses costs, model tiers, and what each tier returns, which is critical for an agent making a paid call. It explains the analysis process (trends, feed data) and the nature of the output (viral score, brief, suggestions, draft). This exceeds the typical minimal disclosure and provides actionable expectations.
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 reasonably concise and front-loads the core purpose, then details tiers, usage, and cost. Each sentence contributes essential information without redundancy. It could be slightly tighter, but the structure is logical and the length is appropriate for the complexity.
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?
Since there is no output schema, the description must explain what the tool returns, and it does: standard returns viral score + brief + suggestions; premium adds deeper analysis and a full draft. It also covers cost and the usage context. This is comprehensive enough for an agent to know what to expect and when to call it. Minor gaps like error handling are not critical for this type of 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 input schema has 100% description coverage, so all parameters (prompt, tier, submolt) are already documented. The description adds no new parameter-level meaning beyond what the schema states; it merely reiterates tier costs and capabilities that are already in the enum description. Thus, the description does not compensate or enhance parameter understanding 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 opens with a specific verb and resource: 'Get AI-powered viral content advice for Moltbook posts.' It then details what the advice includes (score, angles, formats, titles), which makes the tool's function unmistakable. It clearly distinguishes itself from sibling data-retrieval tools like get_moltbook_sample or get_moltbook_digest by focusing on analysis and advice rather than raw data.
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 states when to use it: 'Use this before writing a post to maximize engagement.' This gives clear context for the agent. While it does not enumerate alternatives or exclusions, the unique purpose among siblings is evident, and the usage timing is specific enough to guide correct invocation.
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 are provided, so the description carries the full burden. It discloses that the tool is free, rate-limited to 1 request per 5 minutes, and requires no API key. It also states what the response includes. This goes beyond a simple 'get' verb and provides meaningful operational context for a read-only, no-parameter tool. It could mention behavior on rate-limit violation, but that is minor.
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 tight two-sentence structure: the first sentence states the purpose and content, the second covers return fields and constraints. Every clause carries information, and the most important details are front-loaded. There is no fluff or redundancy.
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 no-parameter tool with no output schema, the description covers the essentials: what it does, what it returns, rate limits, and authentication requirements. It does not compare to siblings or explain how to retrieve historical data, but those are not necessary for invocating this specific tool correctly. The only slight gap is the lack of sibling routing, which is already scored under usage guidelines.
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 tool has zero parameters, and the input schema is empty, so schema coverage is effectively 100%. According to the rubric, the baseline for 0 parameters is 4. The description does not need to explain parameters since none exist, and it correctly omits any such 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 identifies the resource as the 'Moltbook community digest' and the action as retrieving the latest hourly version. It enumerates the content (sentiment, trending topics, narratives, discussions) and the return fields (title, summary, markdown, sentiment scores, narrative tracking). This distinguishes it from siblings like get_moltbook_sample (sample) and get_moltbook_history (history) by emphasizing the hourly, latest nature.
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 the latest hourly digest ('latest hourly', 'past hour') but does not explicitly mention alternatives or when not to use it. There are many Moltbook-related siblings, but the description never directs the agent, e.g., 'for historical data use get_moltbook_history'. The context is clear about recency, but no exclusions or alternatives are named.
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 bears full responsibility for behavioral disclosure. It explicitly discloses the monetary cost ($0.03 USDC via x402), a critical behavioral trait, and mentions the polling mechanism and batch limit. The verb 'Get' implies a read-only nature, and the description adds value beyond the tool name by flagging cost and usage patterns.
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?
Three sentences, each adding distinct value: purpose and limit, polling mechanism, and cost. The purpose is front-loaded, and there is no filler or repetition. Efficient and well-structured.
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?
Covers the essential aspects for a read-only getter: limit, polling, filtering, and cost. No output schema exists, so return format is not expected. It does not discuss alternatives, but the description is self-sufficient for an agent to decide whether to call it given the batch and polling context.
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 three parameters with descriptive text (coverage 100%). The description repeats the polling and confidence details without adding new semantic meaning beyond what the schema already states. Baseline 3 is appropriate when the schema fully documents parameters and the description offers no additional parameter-level insight.
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 states a specific verb ('Get'), a specific resource ('batch of Polymarket predetermined outcome signals'), and a clear limit (up to 20). It distinguishes from sibling get_polymarket_signal by being a batch operation, and the term 'predetermined outcome signals' clarifies the data type. No ambiguity remains about what the tool does.
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?
Provides clear context for when to use: for batch retrieval, for polling via the 'since' parameter, and for confidence filtering. However, it does not explicitly name alternatives or exclusions among the many sibling tools (e.g., get_polymarket_latest or get_polymarket_signal), so it offers clear context but lacks explicit 'when-not' guidance.
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 are provided, so the description carries the full burden. It discloses the access model explicitly ('Free, no payment or API key required'), which is valuable behavioral context about auth/prerequisites, and states what the tool returns. It does not cover rate limits or freshness guarantees, but for a read-only fetch tool the disclosure given is solid.
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 tight sentences: the resource and nature are front-loaded, then return contents, then the access model. Every clause earns its place with no filler, and the most decision-relevant facts (what it is, what it returns, that it's free) appear first.
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 zero-parameter, no-output-schema tool with no annotations, the description is nearly complete: it specifies the data sources, the return fields, and the access constraints. Minor gaps remain (what 'top insights' contains, any freshness window), but an agent can already call this correctly with no further research.
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 tool has zero parameters and schema coverage is 100%, so there is nothing for the description to document beyond what the empty schema already conveys. Baseline 4 applies; the description adds no parameter burden to compensate for.
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 states a specific verb+resource ('Get the latest Pulse narrative intelligence brief'), defines the subject matter (cross-source AI/business narrative tracking from Reddit, HN, GitHub, HuggingFace), and enumerates return contents (title, summary, top insights, narrative count). This distinguishes it from the many pulse siblings (get_pulse_latest, get_pulse_narratives, get_pulse_narrative_detail) by framing it as the digest-style 'brief'.
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 'latest ... brief' phrasing implies it is the top-level summary tool, but there is no explicit when-to-use vs. alternatives guidance. With 23 siblings including pulsing tools of overlapping meaning (get_pulse_narratives, get_pulse_narrative_detail, get_pulse_latest), naming the routing conditions would materially improve selection accuracy.
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 are provided, so the description carries the full responsibility. It discloses the cost ($0.01 USDC via x402) and explicitly lists what the detailed view contains (content items, source breakdown, stage history). The verb 'Get' implies a read-only operation, though it's not stated explicitly. It does not mention authentication or rate limits, but for a read-only tool with cost disclosure, this is reasonably 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?
The description is exactly two sentences. The first sentence front-loads the primary purpose and deliverables. The second sentence provides usage guidance and cost. Every clause contributes value, with no filler or redundancy.
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 single parameter, no output schema, and no annotations, the description covers the essential operational context: what the tool does, what it returns, the prerequisite step, and the cost. Minor gaps include lack of error-handling guidance or behavior for invalid IDs, but these are not critical for an agent to invoke the tool 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?
The only parameter 'id' has 100% schema description coverage ('Narrative ID (from get_pulse_narratives)'). The description repeats this in the text ('Use get_pulse_narratives first to find narrative IDs') but adds nothing beyond what the schema already states, such as format or constraints. With high schema coverage, the baseline of 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 verb 'Get' and the resource 'detailed view of a specific Pulse narrative', and lists the specific components returned (full content items, source breakdown, stage history). It distinguishes this from get_pulse_narratives by indicating the latter is for finding IDs, 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 explicitly instructs to use get_pulse_narratives first to find narrative IDs, providing clear context on the prerequisite. It also mentions the cost, which influences usage decisions. However, it does not explicitly state when not to use this tool or name alternatives beyond the implied one, so it lacks an explicit exclusion clause.
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 full burden. It discloses the tool's return contents (status, job statuses, connectivity) and explicitly states that no payment or API key is required, which covers authentication behavior. It does not explicitly mention read-only, but that is implied by 'check' and the nature of a health endpoint; overall, it provides sufficient behavioral context.
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, well-structured sentence that front-loads the purpose, lists concrete return details, and adds the auth note at the end. Every word adds value; there is no padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description is complete: it explains what the tool does, what it returns, and that it requires no auth. No further context is needed for an agent to call 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?
The tool has zero parameters, and schema description coverage is trivially 100%. There are no parameters for the description to clarify, so the baseline of 3 applies. The description adds nothing about parameters because none exist, which 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 tool checks API health and service status, listing specific return items (overall status, active job statuses, x402 connectivity). It is distinct from all sibling tools, which focus on data retrieval (intelligence, tokens, etc.), so purpose is 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 gives context that this is for checking API health and status, and notes it is free with no auth required, implying when to use it. It does not explicitly exclude alternatives, but given its unique purpose among siblings, the context is clear enough without naming them.
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 behavioral disclosure. It explicitly states the frequency, the time window, the rate limit (1 request per 5 minutes), and that it is free with no API key required. It does not describe the output structure or whether it returns raw data or a formatted digest, but the phrase 'AI analysis' and 'organized by category' gives some indication. Given the absence of annotations, this is solid disclosure.
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, well-structured paragraph that front-loads the core purpose first, then adds operational details (schedule, rate limit, cost). Every sentence provides valuable info: purpose, content specifics, frequency, and requirements. It is concise with no filler or redundancy, making it easy for an agent to scan and extract key facts.
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 no-parameter, no-output-schema tool, the description covers all essential aspects: what it does, when it runs, how often, and access constraints. It does not detail the exact output format, but that may be acceptable for a digest that is likely a human-readable summary. The presence of sibling tools like get_github_repos and get_github_history suggests some overlap, but the description's focus on 'trending repos digest' differentiates it sufficiently. It is largely complete for an agent to decide whether to call it, though minor gaps exist around output specifics.
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 tool has zero parameters, so the baseline is 4. The description adds semantic meaning about what the tool returns (a digest of GitHub trending repos, analysis, categories, language trends, notable projects) which helps an agent understand the tool's behavior even though no parameters exist. This exceeds the baseline by enriching context without any parameter documentation needed.
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 states a specific verb ('Get'), a clear resource ('GitHub trending repos digest'), and the distinctive nature of the content ('AI analysis of newly created repositories gaining traction, organized by category'). It also differentiates from sibling tools by focusing on GitHub specifically, and the phrase 'latest daily' clarifies the scope. This is unambiguous and distinct from the other digest tools.
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 provides useful operational context: it runs daily at 06:00 UTC, scans repos created in the last 24 hours, and is rate limited. It does not explicitly state 'use this when you need GitHub trending repos' or contrast with alternatives like get_github_repos or get_github_history, but the resource and scope are implied strongly enough and the schedule adds practical guidance. It lacks explicit exclusions, but the clarity of purpose compensates.
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. It discloses important behavioral traits: the 7-day maximum window, pagination, return content (full analysis with backtest results), and the $0.03 cost via x402. This goes beyond the minimal and is highly useful for an agent.
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 core purpose and then covering filters, return data, and cost. Every sentence earns its place, with no redundancy or fluff.
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?
Despite having 7 parameters and no output schema, the description covers the essential decision factors: what the tool does, constraints (time window, pagination), filter options, return content, and cost. It does not describe error cases or the exact output structure, but it provides enough for an agent to decide whether and how to call it.
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%, so the baseline is 3. The description adds value by explicitly summarizing the filtering dimensions (chain, tier, minScore) and noting the 7-day window constraint, which is not in the schema's parameter descriptions. This helps an agent understand the relationship between parameters and the overall query.
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's purpose: retrieving historical token signals within a date range, with additional filtering and pagination. The verb 'Get' plus the specific resource 'historical token signals' differentiates it from siblings like 'get_token_signals' (current signals) and 'get_tokens_latest'.
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 provides clear context that this is for historical queries ('by date range'), distinguishing it from real-time signal tools. However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of a full 5.
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 exist, so the description carries full responsibility for behavioral disclosure. It reveals the rate limit (1/20min), the lack of authentication requirements, and the hourly update cadence. It does not cover error behavior or response format, but for a simple sample endpoint these are acceptable gaps. The disclosed traits align with what an agent needs to call it safely.
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 front-loaded with the core purpose in the first clause, then adds distinguishing features (sample vs live), operational constraints (rate limit, auth), and a pointer to alternatives in a compact, logical flow. Every sentence earns its place with no fluff or repetition.
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 tool has no output schema, so the description must convey what the sample contains. It does so by listing the data categories, update frequency, and constraints. Lacking explicit return format (e.g., JSON structure) is a minor gap, but the tool's purpose and contents are sufficiently clear for an agent to decide whether to call it.
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?
With zero parameters and 100% schema coverage (trivially), the description has nothing to add about inputs. The baseline of 4 for no-param tools is appropriate; the description does not omit any necessary parameter guidance because there are none.
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 states a clear verb ('Get') and resource ('free sample of the Moltbook community digest'), and enumerates the content categories (sentiment, topics, narratives, discussions). It immediately distinguishes itself from the sibling get_moltbook_digest by explicitly labeling itself as a 'sample' versus 'live data'. No ambiguity about what this tool returns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly directs the agent to use get_moltbook_digest for live data and provides the alternative's rate limit (1 req/5min) and the option of an API key. It also states when this tool is appropriate (free sample, no key required) and its own rate limit (1/20min). This covers both when to use and when to switch.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden and does it well. It discloses the rate limit (1 per 20 minutes), the generation frequency (every 4 hours), that no payment or API key is required, and that the data is a sample rather than live. This gives an agent a clear behavioral profile before invocation.
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 well-structured and front-loaded. The first sentence states the primary purpose, the second lists what data is included, and the remaining sentences cover frequency, rate limit, access requirements, and the alternative. Every sentence adds value; there is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple no-parameter tool with a rich description, this is complete. It covers what the tool returns (synthesis of multiple data domains), data freshness (every 4 hours), access constraints (rate limit, no auth), and directs to the sibling tool for live data. An agent can correctly decide whether to call it without opening any schema.
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?
There are no parameters, so the baseline is 4. The description adds context about authentication (no API key required) which is not parameter-related, and since schema coverage is 100% (empty schema), nothing additional is needed. It accurately reflects the parameter-less nature.
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 (get) and resource (free sample of Master Intelligence Digest), and elaborates on the content (cross-domain synthesis of multiple data sources). It also explicitly differentiates from the sibling tool get_intelligence_digest by framing this as the free sample versus the live paid version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives explicit guidance on when to use this tool (for a free sample) and directs users to get_intelligence_digest for live data, mentioning the cost and alternative access method (sign up for a free API key). The rate limit and no-payment condition are also stated, so an agent knows exactly when and how to use it.
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:

[![moltalyzer-mcp MCP server](https://glama.ai/mcp/servers/jcislo/moltalyzer-mcp/badges/card.svg)](https://glama.ai/mcp/servers/jcislo/moltalyzer-mcp)

Score Badge

Copy to your README.md:

[![moltalyzer-mcp MCP server](https://glama.ai/mcp/servers/jcislo/moltalyzer-mcp/badges/score.svg)](https://glama.ai/mcp/servers/jcislo/moltalyzer-mcp)

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/jcislo/moltalyzer-mcp'

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