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

With no annotations, the description carries the full burden, and it does disclose two non-obvious traits: the call is instant and it is a paid operation ($0.02 USDC on Base), which matters for agents managing spend. It says nothing about failure behavior for malformed or unreachable URLs, rate limits, or what the prioritized-fix output actually looks like.

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?

One compact sentence front-loaded with the action and the deliverable. The cost note is appended efficiently rather than buried. Nothing in it is wasted, though it could shed the 'Website Modernization' ornament.

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 one-parameter tool with no output schema and no annotations, the description supplies the essentials an agent needs to decide and invoke: what it produces (0-100 scorecard with prioritized fixes) and the payment requirement. Error handling and response format remain unstated but are minor for this shape.

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?

There is a single parameter with 100% schema description coverage, so the schema already documents 'url'. The description adds no format guidance (e.g. scheme requirements, whether redirects or subdomains are followed), so this sits at the baseline for fully covered schemas.

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?

States a specific verb ('Run ... Audit') and resource ('Technical SEO & Website Modernization Audit scorecard'), and adds the output shape (0-100 scorecard with prioritized fixes). 'Website Modernization' broadens it slightly, but the resource is still identifiable at a glance and clearly distinct from all listed siblings.

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?

There is no statement of when to choose this tool versus any alternative, no prerequisites, and no exclusions. Usage is only implied by the word 'Audit'; the agent must infer that it should call this when it has a URL to evaluate.

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 behavioral burden. It usefully discloses that the calculation factors spread/commission friction, checks drawdown auto-lock status, and costs $0.01 USDC on Base, but it does not describe the return format or what happens when a drawdown limit is breached.

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, front-loaded sentence that states the core calculation and key modifiers without filler. It is dense with domain jargon, but every clause contributes to the purpose.

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 seven-parameter financial calculation with no annotations and no output schema, the description covers the core purpose and the USDC cost. However, it omits return-value details and breach behavior, leaving some gaps an agent might need to fill.

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

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

Schema description coverage is 100%, so the schema already documents all seven parameters. The description mentions drawdown and spread/commission concepts but does not map them to specific parameters or add syntax beyond the schema, so the baseline of 3 applies.

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 states a specific verb and resource: it calculates exact CFD/Forex lot size and factors in ECN spread/commission friction and prop-firm drawdown auto-lock status. It is clearly distinct from the unrelated sibling tools, but it does not explicitly name or exclude any alternative.

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?

Usage is implied by the domain-specific phrasing (prop-firm risk sizing for CFD/Forex), but there is no explicit when-to-use, when-not-to-use, or alternative-tool guidance. The agent must infer the appropriate context.

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 disclosure burden and delivers meaningful traits: a per-call cost ($0.015 USDC on Base, implying a paid/crypto-settled endpoint), a rejection rule (office PSTN landlines are discarded), and heuristic behavior (phantom wa.me/linktr.ee/marketplace links). What is missing is failure behavior, rate limits, and what happens when no phone or email is found, so it stops short of 5.

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?

A single front-loaded sentence that leads with the verb and audience before enumerating capabilities, with zero filler. It is dense and slightly comma-heavy, but every clause conveys distinct behavior rather than restating the name.

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 2-parameter, no-annotation, no-output-schema tool, the description conveys purpose, cost, accepted input types, and the kinds of data returned (phones, emails, socials, pixels), which is enough to call it correctly. It does not describe the response shape or partial-result behavior, a real gap given there is no output schema, preventing a 5.

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

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

Schema description coverage is 100% for both parameters, so 'Business website, social bio, or marketplace URL' and 'raw business title to sanitize' are already fully documented. The description restates those semantics (brand-name sanitization, marketplace/wa.me URLs) without adding format rules, examples, or validation constraints beyond the schema, so the 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?

A specific verb (Enrich) plus a specific resource (business URL) followed by the exact sub-tasks performed: name sanitization, phantom-link detection, E.164 phone extraction, email/social discovery, pixel detection. It is unmistakably distinct from every sibling tool (trading sessions, SEO audit, markdown extraction), so an agent can select it without opening a schema.

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?

'for SDR/sales outreach' states the intended use case clearly and the enumerated sub-tasks imply when the tool applies (lead research on a given URL). There are no explicit exclusions, no when-not-to-use conditions, and no named alternatives, which keeps it at 4 rather than 5.

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 exist, so the description carries the full burden. It usefully discloses the price ($0.005 USDC on Base) and that the response includes metadata and a token count, but it omits payment mechanics, failure behavior on non-public/inaccessible URLs, and rate limits for a paid operation.

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?

A single sentence that front-loads the core action and folds in the output shape and cost. No 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?

For a two-parameter tool with a fully described schema and no output schema, the description covers the transformation, expected return elements (metadata, token count), and cost. Only payment flow and error conditions remain unstated.

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

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

Schema description coverage is 100%, so both url and maxChars are already documented with format, range, and default. The description adds nothing about parameters, so baseline 3 applies.

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?

States a specific verb+resource: fetch a public webpage and convert it to clean Markdown. The output characteristics (token-efficient LLM Markdown, metadata, token count) are named, and no sibling tool overlaps with this scraping/conversion function.

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?

'Fetch any public webpage' implies the scope of use, but there is no explicit when-to-use, when-not-to-use, or alternative guidance. The public-only constraint is stated but framed as capability rather than a restriction on when to call it.

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 exist, so the description carries the full burden. It does disclose two genuinely useful behavioral facts: data is 'live' (MT5 FVGs) and the call costs '$0.01 USDC on Base', which tells the agent this is a paid invocation. It says nothing about latency, caching, refresh cadence, or failure behavior for illiquid symbols, which matters for a live-market tool.

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?

It is a single sentence with no filler, but it is an unstructured comma-chain of jargon that is not front-loaded toward the decision the agent needs to make. Terms like 'institutional ECN calibrated' and 'spread-to-ATR execution cost ratios' are packed in without ordering or hierarchy, making it hard to scan.

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?

With no output schema, the description must convey return values, and it does list the metric families. However, it never explains what the derived metrics mean (how 'scalping suitability' is scored, what the spread-to-ATR ratio thresholds imply), so an agent knows the field names but not how to interpret the response.

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?

With one parameter at 100% schema coverage, the schema already documents the optional ticker and the omit-for-all behavior, so baseline 3 applies. The description adds nothing beyond listing symbols the schema already covers, and it enumerates roughly ten tickers while the schema promises 14, a minor inconsistency that could confuse an agent about the full universe.

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 verb 'Get' plus the resource 'cfd microstructure' and an explicit enumeration of returned metrics (ECN spreads, commissions, M1 ATR, spread-to-ATR ratios, FVGs) makes the purpose concrete and unmistakable. Sibling tools are entirely unrelated domains, so no differentiation is needed. It falls short of 5 because the sentence describes the payload rather than the analytical question the tool answers.

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?

There is no statement of when to use this tool, when not to, or what alternative to pick. An agent must infer usage purely from the metric list. The only implicit routing cue is the symbol set, which is not framed as 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 the load. It usefully discloses cost (explicitly $0.00), that the data is 'live' rather than cached, and that the operation is an inspection — implicitly read-only. It does not state auth requirements, rate limits, or what 'wallet payment readiness' actually evaluates, leaving gaps for a zero-annotation tool.

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?

One sentence, front-loaded with the most decision-relevant fact (FREE), then the resource and the enumerated return contents. Nothing extraneous and nothing buried.

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?

No output schema and no annotations means the description must explain the return payload, and it largely does by listing catalog entries, tickers, pricing and wallet readiness. Minor gap: it doesn't describe the shape or size of the response, and doesn't clarify what a 'not payment ready' result implies for subsequent calls.

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 takes no parameters, so the baseline is 4. The description correctly implies the tool requires no input and returns catalog data wholesale.

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?

Names a specific verb ('Inspect') and a concrete resource ('live x402 Agent Hub service catalog'), then enumerates the exact contents returned: CFD/Forex tickers, per-call USDC pricing and wallet payment readiness. That content list distinguishes it from all listed siblings (session data, microstructure, risk calculators, SEO/lead/rendering tools). It stops short of explicitly naming a sibling it replaces, which keeps it at 4 rather than 5.

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 use case is implied — this is a discovery/pre-flight tool for the hub's offerings and payment state — but the description never states when to call it (e.g. 'call before invoking any paid hub tool to check pricing and wallet balance') or when not to. The 'FREE ($0.00)' prefix hints at a cost-driven selection rationale, but it is left for the agent to infer.

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 exist, so the description bears the full burden. It usefully discloses the content categories returned (killzones, FVG windows, spread-danger alerts, swap flags) and implies a read-only informational call. But it omits any statement about access requirements, cost/auth (the '$0.005 USDC on Base' fragment is unexplained), latency, or freshness semantics beyond the word 'live'.

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?

It is a single dense sentence with the core purpose front-loaded, which is good. But the trailing fragment '($0.005 USDC on Base)' is unexplained and arguably does not earn its place, muddying rather than clarifying the sentence.

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?

With no annotations and no output schema, the description should carry the whole load. It enumerates what categories come back but gives no sense of return shape (e.g., whether killzones are objects with start/end times or booleans) or of the cost/auth implication of the USDC note, leaving the agent to guess at invocation context.

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?

There is a single optional parameter with 100% schema description coverage, so the schema already explains the ISO-8601 'at' timestamp and its default. The description's 'live' wording is consistent with that default but adds no extra semantics such as how historical evaluation differs from live evaluation.

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 opens with a specific verb ('Get') and names the exact resource and its sub-components (Asian, London Open, NY Open, London Close killzones, Silver Bullet FVG windows, rollover alerts, triple-swap flags). An agent can tell this is a market-session/time-window lookup, which is distinguishable from siblings like get_cfd_microstructure or calculate_prop_firm_risk. However, it never explicitly contrasts itself with get_cfd_microstructure, which is the nearest conceptual neighbor.

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?

There is no statement of when to call this tool versus alternatives, and no sibling is named. The word 'live' hints at real-time monitoring use, but nothing tells the agent when to prefer this over get_cfd_microstructure or when a historical evaluation is appropriate.

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 burden and does disclose key traits: determinism, typo-free output, the return shape (SVG + data URI), and a concrete cost of $0.025 USDC on Base. It stops short of explaining how payment is authorized, whether calls are idempotent, or what happens on payment failure.

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?

One dense sentence with the artifact list front-loaded and the price/output format trailing. Every clause carries information; nothing is padding.

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 an 11-parameter, no-annotation, no-output-schema tool, the description establishes what is produced and at what cost, but leaves the caller unable to determine which optional fields are meaningful for which template or how payment is settled. Adequate to identify the tool, insufficient to invoke it confidently.

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 only 27% across 11 parameters, so the description must compensate. It partially does by naming the three templates and implying sparkline/metric inputs, but says nothing about theme, badge, brandName, subtitle, or accentColor, and never explains that template selection governs which other fields matter (additionalProperties is false).

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?

A specific verb (Render) applied to three named, dimensioned artifacts (1200x630 OpenGraph banner, 1080x1350 social KPI slide, trading signal sparkline card) plus the exact output format (SVG + data URI). No sibling tool produces images, so the differentiation is implicit but unmistakable.

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 template names imply which use case each output serves, but there is no explicit when-to-use/when-not-to-use guidance and no statement of prerequisites for the paid call. An agent can infer intent from the artifact descriptions but must guess about payment flow and preconditions.

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