Forest Factory

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

The description adds genuinely useful behavioral context not in the annotations: a per-call price of $0.004 USDC charged only on successful calls. However, it never explains why readOnlyHint=false despite an inspection-style operation (presumably the payment/caching side effect) or what the tool does to the target URL. Annotations cover openWorldHint, so the remaining gap is moderate.

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?

Two sentences, front-loaded with the action and the value proposition, followed by the pricing note. No filler, no repetition of the title or 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?

With no output schema, the description carries the burden of describing returns, and it does so by enumerating the four result categories and the cost model. It stops short of covering failure/empty-result behavior or whether the inspected page is fetched and cached.

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?

Only one parameter exists and the schema documents it at 100% coverage with its own description. The tool description implies the URL should point at a developer/documentation page but adds no format or constraint detail beyond the schema, so the 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?

The description states a specific verb ('Discover') and resource ('the callable public API behind a developer or documentation page') and then enumerates the exact artifacts produced (base URLs, portals, machine-readable docs, auth docs). This is unambiguous and clearly separable from the preflight/resolve 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?

The phrase 'for integration setup' implies the intended context, but there is no explicit when-to-use guidance, no statement of prerequisites (what kind of URL qualifies), and no comparison to alternatives such as domain_preflight or package_preflight. Usage is inferred rather than stated.

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?

Adds meaningful context beyond annotations: evidence-only reporting, no inventory inference, no reservation/order placement, and a $0.002 USDC cost per successful call. Annotations already cover read-only/destructive/idempotent/open-world hints, and the description does not contradict them.

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 front-loaded sentences: purpose, then behavioral constraints, then pricing. No sentence is wasted.

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 purpose, constraints, and cost, but with no output schema the description should specify the shape of the 'explicit normalized states' and the nested variant object remains opaque. Adequate but incomplete for a tool whose return values are not structured elsewhere.

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 schema documents both url and variant. The description adds no parameter syntax, format, or variant-scoping detail beyond the schema, so baseline 3 applies.

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

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

States a specific verb ('Resolve') and resource ('public product or listing availability') with explicit scope ('normalized states'). It does not name the sibling commerce_buyability, so it stops short of explicit sibling differentiation, but the availability/buyability distinction is inferable.

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?

Provides conditions for use implicitly ('public product or listing availability') and exclusions ('never infers inventory, reserves items or places an order'), but it does not name an alternative or state when to choose commerce_buyability over this tool.

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?

Adds behavior beyond the annotations: it discloses a per-call price ($0.003 USDC per successful call) and clarifies that it is a non-mutating preflight against the target, which offsets the non-obvious readOnlyHint=false. It does not describe latency, failure modes, or rate limits.

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 short sentences, each earning its place: capability, scope boundary, and cost. The key constraint (preflight only) is front-loaded before the pricing note.

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 carries the return-value burden and does so partially by naming possible blockers. Pricing and safety boundaries are covered; the shape of the returned report could be spelled out further.

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 url, variant, and quantity are already documented, including the quantity bounds. The description adds no syntax or format detail for variant (a free-form nested object), 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 and resource: report whether a public item is buyable, with named blocker signals (out-of-stock, unknown). It is distinguishable from most siblings, though it never explicitly contrasts itself with the closest sibling, commerce_availability.

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?

Explicitly frames the tool as a preflight and excludes what it will not do (sign in, buy, create an order, guarantee checkout), which tells the agent when this is and is not the right call. It stops short of naming the alternative tool to use when a real checkout or availability query is needed.

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?

Adds substantial context beyond annotations: the data source (Coinbase Advanced Trade public market data), the single-venue scope, the warning that provider volume denomination is not normalized, and the $0.001 USDC per-successful-call cost, which also plausibly explains the readOnlyHint=false annotation (a call spends funds). It does not reconcile that annotation explicitly or describe error/invalid-product behavior.

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?

Front-loaded with the action and return payload, followed by the exclusion list and the cost line. The negative clause is a long run-on, but every listed exclusion prevents a plausible misuse, so little is wasted.

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 carries the return-value burden itself and does so, naming the three returned fields. Combined with source, scope, exclusions and pricing, an agent has everything needed to call this single-parameter 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?

Schema coverage is 100% and the schema already carries the regex pattern and length bounds, so the baseline is 3. The description goes further by pinning the format semantics ('exact BASE-QUOTE product id'), clarifying that the value must be a literal product rather than a ticker to be resolved.

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 precise verb and resource ('Return one current Coinbase spot-product snapshot'), names the exact key ('BASE-QUOTE product id'), and enumerates the returned fields (venue price, 24h change, 24h volume). It is unambiguous against unrelated siblings like text_hash or domain_preflight.

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 tells the agent when this tool applies (one exact product id, single venue) and effectively when it does not: no ticker inference, no venue aggregation, no account reads, no orders, no executable quote, no forecasts or recommendations. It stops short of naming a specific alternative tool for the aggregation or forecasting cases, so it lands 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?

With annotations present the bar is lower, and the description still adds real context beyond them: the probe is 'bounded', provider uncertainty is disclosed, cost is $0.003 USDC per successful call, and the excluded capabilities are named. The one tension is that annotations set readOnlyHint=false while the description frames this purely as a resolution/read operation — a likely conservative default rather than an explicit contradiction, but worth flagging as unexplained.

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 tight sentences, front-loaded with the core action and facets, then scope exclusions, then the price. No filler, though 'Provider uncertainty is explicit' is slightly abstract and could be folded into the probe clause.

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 single-parameter, no-output-schema tool this covers the essentials: what is queried, which sources are used, what is deliberately not returned, cost model, and reliability caveats. Return shape is undescribed but the enumerated facets give the agent a working expectation.

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?

Only one parameter, and schema description coverage is 100% ('Bare DNS domain name, not a URL, path, IP address or email'). The description's 'bare public domain' reinforces this but adds no syntax, normalization, or IDN guidance beyond the schema, so the 3 baseline 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 ('Resolve') and resource ('bare public domain') and enumerates the exact output facets: registration, DNS, HTTPS/TLS and mail-policy state, plus the data sources (RDAP, DNS, MX/TXT/SPF/DMARC, TLS probe). This is enough for an agent to distinguish it from every listed sibling, none of which operate on domains.

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 usage ('Resolve a bare public domain') and deliberately fences the scope with 'No registrant personal data, vulnerability scanning, mailbox existence or deliverability claim', which tells the agent what requests are out of bounds. However, it never states when to reach for this tool versus another (e.g., package_preflight for packages) or any prerequisite conditions, so usage is only 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?

Adds real context beyond the annotations: open-world public-registry scope, explicit non-goals, and a pricing model ('$0.002 USDC per successful call') that tells the agent this call has a cost and that billing is success-conditioned. It does not cover rate limits or failure modes. Note a mild tension: readOnlyHint=false sits oddly against a description that reads as a pure lookup, though the paid-call semantics likely explain the annotation.

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?

Front-loaded with the core verb and resource, then the exclusions, then price; every clause carries information. The opening sentence is long and multi-clause, but 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?

With no output schema, the description carries the return-value burden and does list the reported fields (existence, resolved version, deprecation/yank, license, runtime requirement), which is enough to call it correctly. It could be more explicit about the response shape or what happens on a miss/unknown version.

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 baseline is 3, but the description adds meaning the schema does not: it clarifies that a version may be resolved to 'current/latest' when unspecified, which explains the optionality of the version parameter. Ecosystem scoping to npm/PyPI is also reinforced in prose.

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 pair ('verify whether a specific npm or PyPI package version exists') and enumerates the exact outputs (existence, current/latest version, deprecation/yank state, license, runtime requirement). It also scopes itself against the sibling family ('public-registry package install preflight') so an agent can place it next to domain_preflight and commerce_availability without ambiguity.

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?

Explicitly frames the intended moment of use ('before installation') and names two exclusions ('does not resolve dependency graphs or perform vulnerability analysis'), which is strong when-not guidance. It stops short of pointing at any concrete alternative tool for those excluded jobs, so it is a 4 rather than a 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?

Annotations declare readOnlyHint=false, openWorldHint=true and non-idempotency; the description adds genuinely new behavioral facts: the $0.002 USDC charge per successful call (which explains the non-read-only annotation), the fixed public info endpoint, and the explicit disclaimer that Forest does not trade, sign, or read a wallet. It also clarifies that the annualized field is simple nominal, not compounded or forecast, which prevents misuse of the return value.

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?

Purpose and returned fields are front-loaded in the first sentence, the scope/limits disclaimer follows, and the price lands last where the agent needs it before committing. Dense but no filler; every clause carries 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?

With no output schema, the description compensates by enumerating the returned metrics, and it discloses cost, endpoint scope and data caveats. What is missing is only minor: no indication of error behavior or how a failed/unavailable coin is reported.

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?

Only one parameter ('coin') and schema description coverage is 100%, so the baseline is 3. The description adds no syntax guidance (e.g., Hyperliquid ticker conventions) and only implicitly reinforces that a single coin scopes each call.

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 precise verb ('Return') and resource ('one current Hyperliquid native perpetual snapshot') and enumerates the exact fields returned (hourly funding, 8-hour equivalent, mark/oracle basis, OI, volume, max leverage). The 'Hyperliquid native perpetual' framing cleanly distinguishes it from sibling crypto_spot_price and the other preflight/commerce tools without needing to name them.

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 rather than stated: the agent can infer this is the tool for perp funding/mark data, and 'one current snapshot' quietly rules out historical queries or batch lookups. However, there is no explicit when-to-use guidance, no statement of when to prefer it over a sibling, and no mention that multiple coins require multiple calls.

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?

Adds real behavior beyond the annotations: source/signature/checksum files are excluded, checksum companions are linked, ties are surfaced as ambiguity rather than silently resolved, private repos and auth are unsupported, and the call costs $0.003 USDC. Annotations only give generic safety hints, so this carries substantial extra context.

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 paragraph where each clause carries information: exclusion rules, ambiguity policy, auth scope, and price. It is dense but not padded, though the pricing/auth clauses could be split for scannability.

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 should convey what comes back; it does describe the resolved asset, linked checksum companions, and the ambiguity outcome. Missing detail on the actual response shape or error/not-found behavior keeps it from 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%, so os/arch/release/repository/allow_prerelease are already documented. The phrase 'normalized OS/architecture target' lightly reinforces the enum semantics, but adds little beyond what the schema states. 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 precise verb+resource: 'Resolve a public GitHub release into the most plausible downloadable asset for a normalized OS/architecture target.' No sibling (api_discover, package_preflight, etc.) does GitHub release asset resolution, so the tool is unambiguously distinguishable without opening the 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?

The description implies usage (pick a release asset for a target OS/arch) but never states when to use this versus alternatives, nor any preconditions beyond 'public repositories only, no auth.' That constraint is useful but is an exclusion, not routing 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?

It adds substantial context beyond the annotations: local-only execution with no network request, rejection of invalid encodings and non-UTF-8 decoded bytes, the 100 KiB output bound, and a per-successful-call price. One caveat: a purely local, deterministic transform sits awkwardly against openWorldHint=true and idempotentHint=false, though this is a mild tension rather than a direct contradiction.

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?

Two dense sentences that are well front-loaded: the transform first, then behavior and limits, then price. Every clause carries information, though the second sentence is packed tightly enough to border on overload.

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 carries the return burden, and it only implies the response (encoded or decoded text) without stating the shape. For a simple two-mode transform with rich validation detail, this is a minor gap rather than a blocking one.

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 nominally 100%, but the schema descriptions are boilerplate ('Public value value used to scope this lookup'), so they convey no real meaning. The description compensates by explaining the mode values (encode/decode), the variant values (standard vs URL-safe), and that the input is bounded UTF-8 text.

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 names both specific verbs (encode/decode), the exact resource (Base64 / UTF-8 text), and the scope constraint (bounded, caller-supplied UTF-8). An agent can distinguish this from the sibling text_hash without opening either 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?

It implicitly routes the caller between the two modes ('encode ... or decode canonical Base64 back'), but gives no explicit when-to-use/when-not guidance and never names the adjacent text_hash alternative. Usage is inferable rather than stated.

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?

The description states the operation is deterministic and that 'no network request or external provider is used', but the annotations declare openWorldHint=true and idempotentHint=false. A pure, deterministic local hash is by definition idempotent and closed-world, so the declarations conflict with the stated behaviour. This is an annotation contradiction.

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 core capability is front-loaded, followed by constraints, the interpretation caveat, and finally pricing — a sensible order with little waste. It is dense but not padded; only the pricing sentence could be considered non-essential.

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 correctly compensates by specifying the return format (hex plus Base64), plus the input bound, determinism, and the cost model. The one meaningful gap is the missing default algorithm for an optional parameter, and no error behaviour is described.

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% and the enum already enumerates sha256/sha512, so the schema carries the parameter burden and baseline 3 applies. The description usefully confirms the 100 KiB bound and names both algorithms, but adds no syntax or default-value guidance (notably the algorithm parameter is optional yet no default is given).

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 names a specific verb (hash), the resource (caller-supplied UTF-8 text), the two supported algorithms, and the exact output shape (hexadecimal and Base64 digests). That is enough for an agent to separate it from the encoding sibling text_base64 without opening any 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?

It supplies one real usage boundary — digests are not proof of authenticity or password security — which tells the agent when the result should not be relied on. However, there is no explicit routing versus siblings such as text_base64, and no statement of prerequisites beyond the price. Usage is implied rather than prescribed.

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