Open Source Intelligence MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses behavioral traits: cost ($0.50), payment flow (402 handling), default date (today UTC), output type (no prose), and optional authorization bypass. It also mentions a free-tier counter via agent_id, indicating rate limiting.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient with three substantive sentences. It front-loads the primary purpose and then covers payment details. Could be slightly more structured (e.g., separate payment section), but no extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists and the tool has moderate complexity (payment, sibling relation), the description covers all necessary aspects: purpose, cost, payment flow, default behavior, and authorization bypass. It is complete for an agent to decide or invoke.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds context for payment_tx and agent_id (e.g., 'scopes the free-tier counter') but does not substantially extend beyond what the schema already documents. The payment flow explanation provides some added meaning, but not enough to exceed baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: 'Get the top 5 signals from today's brief as structured JSON'. It distinguishes itself from the sibling 'daily_brief' by calling itself 'a cheap sample', making the specific verb and resource unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context for when to use: 'so an agent can decide whether to buy the full brief'. It implies an alternative (daily_brief) but lacks explicit 'when not to use' guidance. The payment and re-call instructions are clear usage steps.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses behavioral traits: cost ($0.01 after 25/day free), payment failure handling (402, Solana memo, re-call with payment_tx), and data sources. There is no contradiction with annotations (none provided).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured, front-loading the purpose ('Compare... side by side') and progressing to sources and payment details. It is not overly verbose, but could be slightly tighter (e.g., merging payment sentences).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (4 parameters, payment model, multiple sources) and presence of output schema, the description covers input usage, payment handling, and error recovery comprehensively. No critical gaps remain 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

While schema coverage is 100% and baseline is 3, the description adds value beyond schema by specifying 'max 10' for packages and explaining the payment flow context for payment_tx. This extra information helps the agent use parameters correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Compare open-source packages (npm or PyPI) side by side in one ecosystem' listing specific metrics (downloads, maintenance, dependents, etc.). It distinguishes from siblings like dependency_risk or license_check by being a comparative, decision-making tool ('which of these should I pick?').

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly frames usage as 'the which of these should I pick? tool', indicating when to use it. It provides context by naming data sources and payment flow. However, it does not explicitly exclude cases or mention alternative tools, so guidance is clear but not exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full transparency burden. It discloses payment necessity, how to handle payment flows (x402 and Stripe), and that briefs expire at midnight UTC. Does not mention rate limits or output format, but covers the most critical behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with a clear first sentence for the core purpose, followed by content list and payment details. It is a bit lengthy but each sentence adds necessary context; no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paid tool with 4 parameters and an output schema, the description covers all essential aspects: what the brief contains, payment mechanisms, re-call flow, date handling. No gaps for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. Description adds meaning: 'date' defaults to today UTC, 'agent_id' scopes a free-tier counter, 'payment_tx' is for re-call after 402, 'stripe_token' is an alternative payment method. This enriches parameter understanding beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it 'get the curated daily open-source intelligence brief' and enumerates specific contents (trending repos, dependency risks, deprecated packages, growth projects). This distinguishes it from sibling tools like 'trending_repos' or 'dependency_risk' which focus on individual components.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description provides explicit usage context: payment required ($5 USDC), default date, expiration, and the re-call protocol after a 402. It does not explicitly contrast with siblings but the payment info is crucial for correct invocation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 cost structure ($0.02/query after 25 free), payment flow for 402 errors, and data sources. However, it omits details like rate limits, data freshness guarantees, or side effects, leaving gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise: three sentences cover purpose, use case, and sources, plus a separate paragraph for payment. It is front-loaded but could be better organized by separating pricing from usage context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and 100% schema coverage, the description adequately covers the tool's purpose, input parameters, and the payment workflow. It also mentions what the risk score includes, making it fairly complete for a paid API tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear parameter descriptions. The description adds value by listing the analyzed fields (output) but does not enhance parameter understanding beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes dependency vulnerability/risk, listing specific aspects (maintenance status, last update, download trends, etc.) and positions it as the 'should I add this dependency?' tool, distinguishing it from siblings like project_health.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly frames the tool as the decision-maker for adding a dependency, indicating when to use. However, it does not provide explicit when-not-to-use scenarios or mention sibling tools like compare_packages as alternatives, so it lacks full guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses the data source (GitHub API), cost (free), and output components (license type, permissions, etc.), but does not explicitly state it is read-only, mention rate limits, or describe error handling. Adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the action and resource, then lists key outputs concisely. No wasted words; the structure is ideal for quick scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description does not need to detail return values. It provides a sufficient overview of what the tool does and its outputs. A minor improvement would be to mention that the repo must exist, but overall it is complete for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description adds no new meaning beyond the schema. The schema already describes 'repo' with an example and notes that 'agent_id' and 'payment_tx' are unused for free tools. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks open-source license compatibility for a GitHub repository, listing specific outputs (license type, permissions, restrictions, commercial-use eligibility, compatibility guidance). It is distinct from all listed sibling tools, which cover summaries, comparisons, dependency risk, project health, and trending repos.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when needing license compatibility info but provides no explicit guidance on when to use versus alternatives, nor any exclusions or prerequisites. The 'FREE' tag is noted but not expanded.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It indicates the tool is free and informational, but does not explicitly state it is a read-only, idempotent endpoint. It also does not mention any rate limits, authentication needs, or side effects. Given the simplicity (no parameters), the lack of detail is acceptable but could be improved.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, using a single sentence that front-loads the core topic ('FoundryNet Data Network info + MINT Protocol details') and then lists specifics. Every word adds value, and there is no unnecessary repetition or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters and an output schema exists (though not shown), the description provides a clear overview of the returned information. It lists the sister servers, which adds value. However, it does not explain what 'attest' means or whether any prerequisites exist, which could be helpful for agents unfamiliar with MINT Protocol.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and schema coverage is 100%, so per guidelines the baseline score is 4. The description does not need to add parameter information since none exist. It appropriately focuses on the return value instead.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides 'FoundryNet Data Network info + MINT Protocol details' and lists what it returns (attestation method, MINT endpoint, sister servers). However, it lacks an explicit verb like 'retrieve' or 'get', which slightly reduces clarity. It distinguishes well from sibling tools that focus on specific analyses.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'FREE' but provides no guidance on when to use this tool versus alternative tools. It does not state prerequisites, when not to use it, or suggest any specific usage context. Compared to sibling tools that are clearly for analysis tasks, this tool's role as a foundational info provider is implied but not explicitly articulated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It fully discloses the paid nature, daily free allowance, payment flow, source (GitHub API), and the composite health score components. There are no hidden behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat long but efficiently packs all necessary information: purpose, metrics, source, payment details, and error handling. It is front-loaded with the tool's purpose and organized logically. A minor trim could improve conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists, the description does not need to explain return values. It covers input parameters comprehensively, payment flow, and error recovery. For a tool with payment complexity, this is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each parameter already has a description. The description adds value by explaining repo format ('owner/name'), agent_id scoping the free tier, and payment_tx for re-calls. The payment context is crucial and goes beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it checks open-source project health for a GitHub repository, listing specific metrics (stars, forks, open issues, etc.) and a composite health_score. It explicitly frames the tool as 'the "is this project alive and worth depending on?" tool,' which distinguishes it from sibling tools like compare_packages or dependency_risk.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool (checking project health) and how to handle payment (free allowance, 402 errors, re-call with payment_tx). However, it does not explicitly state when not to use it or compare to siblings, though the use case is well implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses key behaviors: query modes (snapshot vs live), payment model (free allowance, per-query cost, 402 retry), and data source (GitHub API).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three well-structured sentences: purpose, query modes, and payment. The payment block is dense but necessary; slightly less concise due to detailed payment instructions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers query behavior and payment, and output schema exists (not shown but noted), so return values are likely documented. No missing critical information for usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds value beyond schema by explaining the free-tier counter scoping for agent_id, and 402 retry logic for payment_tx.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it finds trending GitHub repos with growth metrics and optional filtering, distinguishing it from sibling tools like daily_brief or project_health.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains when to use unfiltered vs filtered queries (snapshot vs live) and provides payment instructions, but doesn't explicitly contrast with sibling tools or give when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.