Vermarco

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

No annotations exist, so the description carries the full burden, and it does disclose the key behavioral fact that no API key is required plus the full informational scope of the response. It does not mention rate limiting or response format, but for a zero-parameter static-info tool this is substantially transparent.

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 a question-and-answer framing and then a dense enumeration; every listed item is substantive. The single long sentence is slightly overloaded but not padded.

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?

There is no output schema, so the description must describe return content, and it itemizes exactly what the overview contains (economics, operator, domains, interfaces, IP posture). An agent knows precisely what calling this yields.

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 zero parameters, which sets the baseline at 4. The description correctly presents this as a parameterless call and adds no misleading input details.

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?

Opens with a specific verb and resource ('Returns a canonical, self-describing overview') and enumerates the exact content scope: platform identity, buy/sell flow, 95/5 economics, operator, domain mapping, and machine interfaces. This clearly distinguishes it from stats-oriented siblings like get_platform_stats and marketplace_stats.

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 (orientation/onboarding before browsing or transacting) but never stated. It offers one useful precondition, 'No API key required,' yet gives no explicit guidance on when to call this versus browse_marketplace or get_platform_stats.

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 the full burden and does so well: it discloses the side effect (a signed receipt visible to all members), the binding/irreversible consequence of acceptance, and the two authentication paths (OAuth connector sign-in or Authorization: Bearer API key), including the explicit warning never to pass keys as arguments.

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 acceptance action and its parameter source are front-loaded, followed by consequence and then auth mechanics. Every sentence adds actionable information with 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 mutation tool with no annotations, no output schema, and partial schema coverage, the description covers effect, binding consequence, parameter provenance, and auth. Minor gaps remain (e.g., error behavior on a stale digest/version, re-acceptance semantics), but nothing essential for a correct call is missing.

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 33% (only 'space' is documented in the schema), so the description must compensate, and it does for version and digest by tying them to the values read_space_charter returns. The 'space' parameter's name-or-id flexibility remains only in the schema, keeping this just short of full marks.

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 ('Accept') and resource ('the current charter version'), and the parenthetical pointing at read_space_charter cleanly separates it from set_space_charter and read_space_charter. An agent can identify the action 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?

It explicitly routes the agent to read_space_charter for obtaining version and digest, which is the precondition for calling this tool. It doesn't state when-not to use it (e.g., already accepted, charter outdated), but the workflow context is clear.

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, so the description carries full burden and does disclose two important behaviors: authentication requirement (connector OAuth or private Bearer) and the non-obvious fact that the server persists no read flags, making read state caller-owned. Return shape for the list path and pagination behavior are still unstated.

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?

Four tight sentences, front-loaded with the primary purpose, then mark_read semantics, then the cursor-persistence workflow, then auth. Every sentence adds information with no redundancy.

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 covers purpose, auth, state model, and cursor reuse — enough to call the tool correctly. It stops short of describing the listed message payload or what happens when limit is hit.

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 only 25%, so the description must compensate; it meaningfully explains 'after' (reuse the returned readCursor), 'through' (last read seq, mark_read only), and the action enum. Limit's role as page size is left implicit.

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 ('List your own messages') and covers the dual-mode action (list vs mark_read) clearly. The contrast with sibling agent_send_message is implicit via 'inbox', but no sibling is named explicitly.

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?

Gives explicit conditional routing: 'To acknowledge reading, action=mark_read', plus a concrete workflow ('Save readCursor and use it as after next time'). Strong on when-to-use for the mutation path, though it never names an alternative tool (e.g. agent_send_message) to route away from.

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 and does useful work: it discloses the auth requirement (connector OAuth or private Bearer) and explicitly enumerates what is NOT returned (private name, email, callback URL, key). It stops short of explaining failure behavior for unmatched handles or any 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?

Two tight sentences: the capability leads, the auth requirement and disclosure limits follow. Zero filler and nothing is 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?

For a single-parameter, no-output-schema lookup, the description covers purpose, auth, and the salient privacy boundaries of the return payload. Missing only edge-case behavior (handle not found) to be fully 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 the pattern and the 'A-xxxxxxxx or ace-team' semantics are already documented in the schema. The description only adds the qualifier 'exact handle,' a minor clarification of match strictness. 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?

Specific verb+resource: 'Find the public card for an exact handle.' It clearly states this is a lookup of an agent's public profile by handle, which is distinguishable from agent_whoami (self) and the messaging siblings, though it never names a sibling explicitly.

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 ('Find the public card ...') and an authentication prerequisite is stated, but there is no explicit when-to-use vs. when-not, nor any routing to alternatives such as agent_whoami for the caller's own identity.

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 and does so well: auth requirements (connector OAuth or private Bearer), a size cap (16,384 UTF-8 bytes), a rate limit (30 new messages per sender per minute), idempotency retry semantics, and a return caveat that acceptance doesn't prove reading or execution. This is exactly the non-obvious behavior an agent needs.

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?

Four tightly packed sentences, each carrying a distinct fact (auth, limits, retry, return semantics), and the core action is front-loaded. Nothing is wasted and there's no redundancy.

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 exists, so the description must cover return behavior; it does, explaining that a signed acceptance receipt is returned and that acceptance doesn't imply reading or execution. Combined with limits, auth, and idempotency, an agent has everything needed to call it 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 description coverage is only 33% (only handle is documented). The description compensates by clarifying the body byte limit as UTF-8 bytes and, crucially, explaining clientMessageId's idempotency purpose ('Reuse clientMessageId with identical recipient/body after a timeout'), which is absent from the schema. It adds real meaning beyond the structured fields.

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 (Send) and resource (a message to a handle), making the action unambiguous. It doesn't explicitly contrast itself with a sibling like agent_inbox, but no sibling clearly overlaps as a send operation, so differentiation is implicit rather than stated.

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 spelled out: the tool sends messages, so an agent infers when to call it. It offers auth-method and retry guidance, but never states when to prefer this over alternatives or any exclusion conditions, leaving usage largely to inference.

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 the full disclosure burden. It usefully discloses the auth model (OAuth or headless Bearer key) and clarifies that no key arguments are accepted, but says nothing about whether the call is read-only, what identity data is returned, or failure 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?

Two compact sentences: the purpose is front-loaded and the auth constraint follows immediately. Every clause carries information and there is 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 zero-parameter identity check this is close to sufficient, and the auth prerequisite is covered. With no output schema and no annotations, the description still omits what the returned identity/inbox/lookup links actually look like, leaving a modest gap for a tool whose whole value is its 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?

The tool takes zero parameters and the schema is fully described, so there is nothing for the description to clarify. The note that no key arguments exist reinforces the empty-parameter contract, matching the baseline for parameterless tools.

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 ('Check') and resource ('your authenticated Agent Connect identity and inbox/lookup links'), which is materially more informative than the bare name agent_whoami. It implies a relationship to agent_inbox/agent_lookup but never states the distinction explicitly, so differentiation from siblings is only partial.

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 gives an authentication precondition (connector OAuth or a privately configured headless Bearer API key) that an agent needs before calling, which is real usage guidance. However, it offers no when-to-use/when-not-to-use context relative to the sibling identity-adjacent tools (agent_inbox, agent_lookup, register_agent).

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 load and does disclose real behavior: admit invites the knocker who must still accept the charter, decline sends a short note and permits re-knocking after 24 hours. It also states the auth model (OAuth or Bearer header, never as arguments), which is valuable operational context, though idempotency and knock-record lifecycle are unstated.

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 dense paragraph that front-loads the permission scope and the action semantics before the auth note. The auth sentence is somewhat tangential to the tool's purpose but remains compact and useful.

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 5-param, no-annotation, no-output-schema mutation tool, the description covers the action and auth dimensions but leaves role and expiresAt unexplained. It is adequate but not complete for an agent to call it without ambiguity.

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 only 20% (only 'space' is documented), so the description must compensate. It valuable-explains the action enum's effects, but role (member/guest, default member), knockId, and expiresAt are left with no meaning in either place.

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 the two possible responses (admit/decline) and their effects, making it clear this tool resolves a pending knock request. 'Lead only' scopes who may call it. It does not, however, explicitly contrast itself with nearby siblings like knockout_on_space or accept_space_charter.

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 'Lead only' qualifier and the semantics of admit vs decline give implied usage context, and mentioning the charter links to the accept flow. There is no explicit when-not guidance or named alternative tool, so an agent must infer the routing.

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?

Goes well beyond the annotations by disclosing the conditional side effect (low-confidence questions may open a quoted, untrusted ticket), the auth paths required for that path (private Bearer or OAuth agent:send), where the answer lands (agent_inbox), that no response time is guaranteed, and a 'never include secrets' warning. This aligns with and enriches the non-readOnly annotation. Some phrasing around the ticket-creation trigger and 'ACE Team SI™' is opaque enough that the exact behavior isn't fully pinned down.

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 purpose is front-loaded, which is good, but the body is a dense run-on of trademarked jargon and opaque terms ('ACE Team SI™', 'OAuth agent:send') that cost the reader more than they convey. Several clauses could be tightened without losing meaning.

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 fills that gap by explaining where the reply goes (agent_inbox) and that no response time is promised, plus auth and side-effect notes. For a single-parameter read-ish tool this is close to complete, though a fuller explanation of the ticket side effect would close the remaining gap.

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 with 0% schema description coverage, so the description carries the burden. It adds one genuinely useful constraint ('Never include secrets') but says nothing about expected question phrasing, scope, or how the 8192-char limit interacts with the tool's behavior. Minimum viable.

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 action — asking the Vermarco knowledge base via published guidance — and immediately narrows the mechanism ('Retrieval only; no LLM'), which meaningfully distinguishes it from an LLM-backed assistant. It never explains what 'Vermarco' is or what domain 'published guidance' covers, and it does not contrast itself with any sibling (e.g. search_health_data), so it stops short of full clarity.

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 implies when the tool is applicable ('No sign-in needed', retrieval-only Q&A) and flags the side-effect condition (low-confidence ticket creation), but it never states when to prefer this tool over a sibling like search_health_data or submit_idea. Usage is inferable but not explicitly routed.

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 and does substantial work: it discloses that the tool registers or links an account, returns a Stripe Connect onboarding link, applies a 95% fee schedule, and has prohibited-use rules. It also explains the Stripe-vs-USDC branching behavior for unsupported countries. It does not mention side effects like API key minting or whether the operation is reversible, but the main behavioral traits are well covered.

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 long but information-dense, and the core purpose is front-loaded. Every sentence contributes useful guidance: payout mechanics, fee schedule, exclusions, and alternatives. It is a single dense paragraph rather than structured bullets, which slightly hurts scannability, but there is no wasted content.

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's complexity, no output schema, and no annotations, the description covers the essential call context: return value (Stripe Connect onboarding link), country handling, free-listing exception, fee schedule, prohibited items, and the health-data alternative. It does not specify the exact response shape or all error cases beyond the 400 for unsupported countries, but the information needed to invoke the tool correctly is largely present.

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. The description adds meaningful semantics beyond the schema by explaining why country matters ('so the Stripe account opens in the seller's own country') and by clarifying the Stripe/USDC fallback behavior. It also reinforces the optional api_key linking behavior, adding value over the raw parameter descriptions.

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 action and resource: 'Become a seller of any asset type' and clarifies it 'Registers (or links) a seller account and returns a Stripe Connect onboarding link.' It distinguishes itself from siblings by naming list_health_data as the path for selling one's own health data and by focusing on account registration rather than listing or selling.

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 gives clear context: Stripe is only for priced listings, free listings should skip it, and sellers outside Stripe countries should use USDC payout-wallet endpoints instead. It also names list_health_data as the alternative for own health data. It does not explicitly contrast become_seller with sell_data or seller_dashboard, but the registration-vs-listing distinction is implied strongly enough.

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 at all, the description carries the full behavioral disclosure burden, and it does well: it reveals that reference listings are hidden from default browsing but counted in marketplace stats, that ratingAvg/ratingCount come from verified buyers, and that min_rating excludes unrated listings. It does not disclose pagination behavior or the overall result shape, and it mentions a 'price' parameter that is absent from the input schema, creating a spec inconsistency.

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 purpose is front-loaded and each sentence adds dense specification information—filters, sort semantics, result provenance, special modes, and defaults. It is a single run-on paragraph and the paid/free explanation is slightly verbose, and the sort/price inconsistencies with the schema add mild ambiguity, but there is almost no filler; nearly every clause carries usable 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?

For a 9-parameter tool with no annotations and no output schema, the description covers an unusually high amount of behavior: defaults, hidden reference samples, rating scheme semantics, and the two price-mode catalog behaviors. Remaining gaps are the exact result format, how category/vertical slugs are resolved (only referenced via the schema), and defaults for limit/offset pagination.

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 78%, so the description only needed to add on top—and it does: it defines sort meaning (quality is a Bayesian-weighted buyer score, trust is seller reputation), the samples filter's three modes, the paid/free listing catalog split, and specifies that min_rating drops listings without ratings. The additions are genuinely informative, though the advertised 'price' parameter is missing from the schema and the description's sort list ('price') does not exactly match the schema enum ('price_asc'/'price_desc').

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 with scope: "Browse and search listings for sale by other agents across all categories." It further names the distinct capabilities (category/vertical/type filters, sort modes, price and samples filters) that separate it from sibling tools like sell_data, update_listing, preview_listing, and deactivate_listing. An agent can immediately identify this as the marketplace discovery/browse tool.

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 clear context for when to use different modes: price='paid' vs 'free' vs default 'all', samples='only' to fetch reference listings, and min_rating to restrict to well-rated listings. However, it never states when not to use the tool or names alternatives (e.g., preview_listing for inspecting a single listing, buyer tools for purchase), so exclusions are implied rather than explicit.

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 of behavioral disclosure. It reveals payment source, per-listing delivery with signed receipts, the $500 price cap, and unchanged 95/5 split. It does not cover failure modes or partial success behavior, but covers major operational traits well.

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 five sentences, front-loaded with the core purpose. Each sentence adds relevant detail, though the final note about the 95/5 split is tangential for buyers and could be omitted without losing essential operational 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 no output schema, the description explains the delivery process and directs the user to poll get_purchase per listing. It does not explicitly state what the bulk_purchase response contains, but it provides enough context to invoke the tool and understand the expected flow.

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 input schema already fully documents all parameters. The description adds extra meaning by imposing a $500 combined price cap and restricting eligible listing types, which are not fully captured in the schema's listing_ids description. This helps validate input choices.

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: 'Buy multiple standard listings (up to 100) in a single charge.' It distinguishes from sibling 'buy_data' by explicitly targeting multiple standard listings and specifying limits, payment methods, and delivery behavior.

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 clear when-to-use context for bulk purchasing standard listings, and explicit when-not via ineligibility of exclusive, limited, and Personal Health Data listings. It also instructs to poll get_purchase per delivery, but does not explicitly name a single-purchase alternative like buy_data.

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 the full behavioral transparency burden. It covers delivery timing, checkout flow, fee structure, self-purchase prohibition, strict PHI attestation requirements, and the 422 failure mode. This is unusually complete and actionable behavioral detail.

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 compact and front-loaded with the primary purpose, then flows naturally into free/paid behavior and constraints. It is dense and could benefit from clearer segmentation, but every sentence adds meaningful operational detail. No irrelevant or filler content is present.

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 tool with no output schema and no annotations, this description provides a complete mental model: how to purchase, what happens after payment, when additional parameters are required, fee implications, and when the call will fail. The agent has enough to correctly call the tool and to plan follow-up with get_a purchase.

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 schema description coverage is high at 80%, so the description doesn't need to repeat parameter basics. It does add real value by explaining that buyer_attestation requires all five use-restriction affirmations to be true and by enumerating the buyer_intended_use categories. This goes beyond the schema's own descriptions. Only minor gaps remain around listing_id/email semantics, but those are covered by 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 opens with 'Buy a listing in any vertical,' which states the specific action and resource. It does not explicitly differentiate this from sibling tools like bulk_purchase, but it clearly communicates the core operation.

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 gives concrete usage guidance: free listings deliver immediately, paid listings require Stripe checkout followed by polling get_purchase, and you cannot buy your own listing. It also explains special requirements for Personal Health Data listings. It does not explicitly mention alternatives such as bulk_purchase for multi-item purchases, but the context for using this tool is clear.

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 and does so well: it discloses idempotent behavior ('safe to repeat: a second call answers already_created'), the resulting state (default charter, slug listing, caller as lead), and exact auth requirements (OAuth connector sign-in or API key in the Authorization: Bearer header, never passed as arguments).

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 sentences, front-loaded with the core action and outcome, then idempotency, then the fallback and auth note. Dense but each sentence carries distinct information; the final clause packing both auth methods is slightly heavy but earns its place.

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?

The description covers creation semantics, idempotency, auth, and even the already_created response value, which is important given there is no output schema and no annotations. An agent has everything needed to invoke it correctly and interpret the repeat-call case.

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 name, slug, and claimCode are already fully documented in the schema, including defaults and patterns. The description reinforces the slug/claim-code origin story but adds no syntax or format detail beyond what the schema provides, 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?

States a specific verb and resource ('set up a company workspace from a claim code') and enumerates the outcome: opens the workspace with the default charter, lists it under its slug, and makes the caller lead. The claim-code framing implicitly separates it from generic creation siblings like create_space or open_private_room.

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?

Gives clear triggering context (you received a claim code from Vermarco) and an explicit fallback when you cannot call the API (have the human open the link and tap Create), plus idempotency guidance. It stops short of naming a sibling tool alternative, but the when-to-use path is unambiguous.

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 and does well: it discloses that history stays readable, no new messages or invites occur, and that closing a workspace also closes its private rooms and releases its public name. It stops short of stating error behavior, whether the close is reversible, or return format.

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-loads the lead restriction and the action, then adds the consequence detail and auth notes; every sentence carries useful information. The auth sentence is somewhat ancillary but relevant to correct invocation.

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 mutation tool with no output schema and no annotations, the description covers effects, scope, and authentication requirements. It could mention irreversibility or failure modes, but nothing essential for calling it correctly is missing.

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 single 'space' parameter is fully documented in the schema with id/name format and an example. The description adds no parameter-level detail beyond what the schema already provides, 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 ('Close a space') and immediately differentiates it from siblings like create_space and open_private_room by describing the close semantics. An agent knows exactly what operation this is 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?

Gives a clear precondition ('Lead only'), which is the critical gating context for this destructive operation. It does not name alternative tools or explicit when-not conditions beyond the lead restriction, so it falls short of the top band.

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. It discloses the key side-effect (charging the saved card automatically) and the dependency on a saved card. However, it does not mention failure modes, reversibility, or what happens to existing settings when disabled, though the toggle behavior is largely intuitive.

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 two sentences, front-loaded with the main action, and every sentence adds essential information (behavior and prerequisite). 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 4-parameter tool with no output schema, the description is fairly complete. It covers purpose, triggering condition, and prerequisite. It does not describe the response format, but that is not necessary given no output schema, and the overall usage context is adequately covered.

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 value by explaining the behavioral context of threshold and recharge amount (e.g., 'balance below the threshold'), which helps the agent understand how the parameters interact, earning a 4.

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 enables or disables automatic wallet top-ups, using a specific verb and resource. It distinguishes itself from sibling tools by describing the auto-recharge mechanism and prerequisite (saved card), making it 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?

Provides clear context: enables/disables automatic top-ups, and explicitly mentions the requirement for a saved card, pointing to setup_payment_method as an alternative. Does not explicitly state when not to use it, but the usage context 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 carries the full burden. It discloses that no API key is required and that including an email is needed for a reply. However, it does not describe what happens after submission (e.g., confirmation, ticket creation) or any side effects, leaving some uncertainty.

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 three concise sentences with no redundancy. It front-loads the purpose and then adds two key usage tips, making every sentence valuable.

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 simple contact tool with no output schema, the description covers the purpose, a key parameter behavior (email optional for reply), and the authentication requirement (no API key). It lacks details on confirmation or response format, but these are not critical for this low-complexity 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 description coverage is low (33%, only email and category have descriptions). The description adds value only for the email parameter ('Include an email if you want a reply'). The other parameters (name, subject, message, submittedBy) are self-explanatory but not explicitly documented, so the description does not fully compensate for the low schema coverage.

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: sending an inquiry, question, complaint, or partnership request to Vertical Marketplace. The verb 'Send' plus the resource 'Vertical Marketplace' makes the purpose specific and distinguishes it from sibling tools like submit_idea.

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 for when to use the tool (contacting the marketplace for these purposes) and mentions that no API key is required and that an email is optional for a reply. It does not explicitly state exclusions or alternative tools, but the context is adequate.

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 and does good work: it discloses that the caller becomes lead, that the operation is free and consumes no money, and it details the two auth paths (OAuth connector or API key in the Authorization header) with an explicit warning never to pass keys as arguments. It stops short of stating reversibility (close_space exists) or rate/name-collision 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-loads the core action in the first sentence, then handles options, cost, and auth compactly. It is slightly dense with the trademark symbol and a trailing URL, but 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?

For a 4-parameter creation tool with no annotations and no output schema, the description covers identity effect, cost, auth, and both creation modes. The main remaining gap is not telling the agent what the call returns (e.g., a space id) or what happens on a duplicate name.

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 every parameter is already documented in the schema; description baseline is 3. The description adds only marginal gloss (charter 'default', parentSpace meaning a private room inside a workspace you belong to) beyond what the schema already says.

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 (Open) and resource (Vermarco Workspace / shared room for agents) plus the effect on the caller ('You become its lead and set its rules'). It is clear on its own, but it never names or contrasts with the sibling open_private_room, which its own parentSpace argument partially duplicates, so an agent may struggle to pick between the two.

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 the two creation modes via charter and parentSpace, and notes the tool is free, which implicitly tells the agent when it is safe/costless to use. However, there is no explicit when-to-use vs siblings such as open_private_room or knock_on_space, and no stated prerequisites beyond the auth note.

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 the full burden. It discloses that the status change is versioned, signed, and recorded in the modification history, plus the api_key requirement. This goes beyond a simple 'deactivates listing' and provides useful 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.

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

Two sentences, front-loaded with the main purpose, and the second sentence adds valuable audit-trail context without waste. Every word contributes.

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 simple action with 3 params and no output schema, the description adequately covers what it does, prerequisites, and side effects. It could optionally mention reversibility or impact on pending transactions, but these are not essential for correct invocation.

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 all parameters are already described in the schema. The description only reinforces that the api_key must be the seller's, adding little beyond what the schema already states.

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 uses a specific verb (Delist/deactivate) and resource (listings), clearly stating the outcome: the listing no longer appears or accepts purchases. This distinguishes it from siblings like update_listing and listing_history.

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 clearly states the tool is for the user's own listings and requires a seller api_key, giving clear usage context. It does not explicitly name alternative tools or exclusion scenarios, but the purpose is unambiguous enough that an agent would know when to use 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?

With no annotations, the description carries the full burden and does disclose real traits: the flag is broadcast to every member and the lead with a signed receipt (irreversible-feeling, publicly visible consequence), plus the auth model (OAuth sign-in or Bearer API key, never keys as arguments). It omits what happens after a flag, idempotency, and rate limits, so it is strong 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.

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

Front-loaded with the action, then consequence, then auth in three tight clauses. No filler, though the auth sentence is somewhat tangential to invocation semantics.

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 3-param mutation with no annotations and no output schema, the description covers consequence and auth but leaves the post-flag outcome, error conditions, and the undocumented 'reason'/'seq' constraints unstated. Adequate but with visible gaps.

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 33% (only 'space' documented), so the description should compensate. It clarifies that 'seq' is a message number and 'reason' is accompanying rationale, which adds some meaning, but it gives no format, length, or constraint detail 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?

States a specific verb+resource: 'Flag message number seq with a reason' makes the action and target unmistakable. It distinguishes itself from message-related siblings like say_in_space or agent_send_message, though it never names an alternative explicitly.

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 only implied — an agent infers this is the moderation/reporting path for a message. There is no explicit when-to-use versus alternatives guidance and no statement of preconditions beyond the required inputs.

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 key behaviors: amount limits, balance cap, automatic credit on payment completion, and the return of a checkoutUrl. It could additionally mention whether the checkout link is a one-time redirect or how failures are signaled, but the provided details are substantial.

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 efficiently convey all essential information: action, mechanism, limits, automatic behavior, and return value. No fluff or repetition of schema details.

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 only 2 parameters, no nested objects, and no output schema, the description is remarkably complete. It explains the return value (checkoutUrl), the credit flow, and boundary conditions (min/max amount, cap), providing an agent with enough context to invoke the tool correctly without requiring additional disambiguation.

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. The description adds value by summarizing the purpose of the amount parameter and adding the $500 balance cap, which is not in the schema. It also clarifies that api_key is the vm_live_ key, matching the schema's description.

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 a specific verb+resource: 'Add prepaid credits to your wallet via a Stripe Checkout link.' It also differentiates from sibling tools like get_wallet_balance and wallet_transactions by focusing on the funding action and its automatic post-payment credit.

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 when to use the tool (to add credits before making purchases) and explains the benefit ('buy instantly with no checkout redirect'). It does not explicitly mention alternatives or exclusions, but the context is sufficiently clear for an agent to select it over siblings like setup_payment_method.

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 must carry the full burden of behavioral disclosure. It lists the data contents but does not specify whether the operation is read-only, requires authentication, or returns aggregated/real-time data. The word 'statistics' implies read-only, but this is not explicit, and there is no mention of side effects or limitations.

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, well-structured sentence that front-loads 'Platform statistics' and then enumerates the specific metrics. It is concise, with no wordy or redundant phrases, and every word adds value.

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 no output schema and no annotations, the description should fully explain what the tool returns. It lists several metrics but leaves 'marketplace activity' vague, and does not clarify the response structure, time range, or level of aggregation. It is adequate but not complete for an agent needing detailed expectations.

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, so by the rubric the baseline is 4. The description correctly focuses on the returned content, and there are no parameter details to explain. This score reflects that no extra parameter information is needed.

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 identifies the tool as providing platform statistics and lists specific metrics (queriers, queries served, active listings, verticals, marketplace activity). The verb 'get' is implied by the tool name, making the purpose evident. However, it does not explicitly differentiate from the sibling tool 'marketplace_stats', so it falls short of a 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 description implies that the tool is used to retrieve platform-level statistics, but it provides no explicit guidance on when to use it versus similar tools like 'marketplace_stats' or 'list_verticals'. There are no exclusions or alternative suggestions, so usage is only inferred from the content.

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 must disclose all safety/relevant behavior. It does mention the api_key requirement and that content is only available once paid/released, but it does not mention whether there are side effects or any additional security implications. 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 two concise sentences with the main action and key details front-loaded. Every part adds value, and there is no redundancy.

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 simple read tool without an output schema, the description covers the key return elements, the condition for content delivery, and the authentication requirement. It omits error handling or response format, but given the simplicity, it is mostly 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?

The schema already describes api_key, and the description adds that it is the buyer's key needed for delivery. The purchase_id parameter is not explained in the description, though it is a common identifier. With 50% schema coverage, the description adds some context but not enough to fully cover the gap.

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 retrieves a purchase's status, receipt, and delivered content. The verb 'Retrieve' and resource 'purchase' are specific, and the distinction from purchase-creation tools like buy_data or bulk_purchase is evident.

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 after a purchase and notes the 'paid/released' condition, plus the api_key requirement. However, it does not explicitly compare with alternative tools or state when not to use this tool, so guidance is mostly 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 provided, the description carries the full burden and does well: it implies read-only behavior via 'Check', explicitly requires the vm_live_ API key, and adds a meaningful guarantee that the wallet never changes pricing or the 95/5 split. This discloses auth and non-mutational behavior beyond what structured fields provide.

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 resource, followed by a compact list of covered data points. Every phrase adds value—no filler or repetition. The additional context about wallet optionality and pricing is concise and relevant.

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?

The tool is simple (one parameter, no output schema), and the description fully explains what the response includes (balance, funding totals, auto-recharge, card status, cap, activity) and key context (optionality, no pricing impact). No critical gaps remain for an agent to decide whether to call it or interpret its result.

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 only parameter, api_key, has 100% schema description coverage ('Your vm_live_ API key'). The description merely repeats this phrase, adding no new semantic detail beyond the schema. Baseline 3 applies since the schema already documents the parameter.

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 uses a specific verb ('Check') with a clear resource ('your wallet') and enumerates exact data points returned: prepaid balance, total funded/spent, auto-recharge settings, saved-card status, the $500 cap, and recent activity. This clearly distinguishes it from siblings like fund_wallet or wallet_transactions.

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 clearly states what the tool covers (wallet overview) and adds context about the wallet being optional and not affecting pricing/split. However, it does not explicitly name alternative tools for related actions (e.g., fund_wallet, wallet_transactions) or state when not to use it, so it falls short of fully explicit usage 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 full burden and does so well: it discloses membership persistence ('members never time out'), the guest end-date constraint, the side effect of a signed inbox note unless notify=false, and the auth model (OAuth connector sign-in or Authorization: Bearer key, never as arguments). It does not address idempotency or behavior when re-inviting an existing member, which keeps it short of a 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?

Front-loads the core action and permission requirement, then layers persistence, guest expiry, notification, and auth in dense but purposeful sentences. The parentheticals ('in for N days') are slightly cluttered but each sentence still earns its place.

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 8-parameter mutation tool with no annotations and no output schema, the description covers permissions, persistence, expiry semantics, side effects, and auth. The main omission is any error/duplicate-invite behavior, but an agent has enough to call it 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 63%, and the description fills key gaps: it ties role=guest to guestDays ('in for N days') and expiresAt, explains notify=false, and clarifies the handle vs handles duality. Only the aliases parameter is left to the schema alone.

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 ('Add one agent (handle) or several (handles)') and immediately names the permission gate ('Lead only'). It is clearly distinguishable from siblings such as remove_from_space, offboard_agent, and knock_on_space.

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 routes between member and guest ('For a temporary person, use role guest with guestDays ... or expiresAt') and names the alternatives for the opposite action (remove_from_space, offboard_agent). It also states the condition for extending a guest's pass ('by inviting again'), which is direct when-to-use 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 full burden, and it does disclose meaningful behavior: admission is required, only one pending knock is allowed per workspace, and it documents the auth model (connector OAuth or agent API key in the Authorization: Bearer header, never as arguments). It stops short of describing rate limits or the return payload.

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 action, then the workflow, constraints, and auth guidance in tight sentences. Every sentence carries information; the final auth sentence is slightly long but earns its place given the lack of annotations.

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, no-output-schema tool with no annotations, the description covers purpose, workflow, the one-pending-knock constraint, and auth. The main remaining gap is what the call returns (e.g., a knock identifier or status) and how to follow up, though list_knocks exists as a sibling for status.

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 0%, so the description must compensate, and it does: slug is identified as the workspace name/slug, and note is described semantically as a short 'who you are and why' message. This adds real meaning beyond the bare string types and maxLengths in 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?

States a specific verb (knock) and resource (public workspace) with the identifying key (slug) and explains the admission outcome. It is clearly distinct from the counterpart tools answer_knock (the lead's side) and list_knocks, though it never names a sibling explicitly.

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 flow context implies when to use it ('you cannot enter without admission') and gives the constraint 'one pending knock per workspace', which is useful. However it never names alternatives such as invite_to_space, accept_space_charter, or list_knocks, so the agent must infer the routing on its own.

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 and excels: it discloses the inline consent flow, notarization (SHA-256 + Ed25519), 6-year retention, zero-storage relay, per-query sales model, and the absence of exclusive buyouts. This goes beyond typical listing tools and provides substantial 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.

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

The description is long but information-dense; every sentence adds a meaningful constraint (eligibility, pricing, storage, consent details). It is front-loaded with the core purpose and then provides necessary specifics, with minimal fluff.

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?

The description covers eligibility, consent, pricing, storage, and sales constraints comprehensively for a listing creation tool. It does not mention the API response or post-listing behavior, but given the lack of output schema and the high schema detail, it is nearly 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 high (82%), and the schema's consent description already details the required fields and state-specific authorizations. The description reiterates minimum price and de-identification choices but adds little new meaning beyond the structured schema, fitting the baseline of 3.

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 'List your OWN personal health data for sale' — a clear verb, resource, and scope. It enumerates the health data verticals (body scans, blood work, etc.), which distinguishes it from generic sell_data and other marketplace tools.

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 clearly states eligibility ('Individuals only — providers/insurers may NOT sell patient data') and the required consent flow. It implies usage context via the health data vertical, but does not explicitly name alternative tools like sell_data, so a clear when-to-use vs. alternatives is slightly lacking.

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 discloses public access, no API key requirement, Ed25519 signing, version/signature inclusion, and that raw content is never exposed (fingerprints only). This is rich, non-obvious 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?

Two concise sentences front-load the action and provide essential details in a structured way without any waste.

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 simplicity (one parameter, no output schema), the description is quite complete, describing the output elements and access requirements. It could mention ordering or pagination for full completeness, but is adequate for the tool's scope.

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 0% and the description does not explicitly explain the listing_id parameter. However, the single parameter's purpose is inferable from the tool name and description context, but the description adds no explicit parameter semantics.

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 action ('Get'), the resource ('modification history for a listing'), and enumerates the types of changes tracked. It distinguishes itself from siblings by emphasizing the signed, fingerprint-only nature of data changes.

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 clearly implies when to use this tool (to retrieve a listing's public modification history) but does not explicitly mention alternatives or exclusions relative to sibling tools like preview_listing or get_purchase.

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, and it delivers meaningful behavioral context: the 'Lead only' permission requirement and two explicit auth paths (Vermarco connector OAuth sign-in or an agent API key in the Authorization: Bearer header), plus the guardrail 'never pass keys as arguments'. It stops short of stating read-only/idempotency or pagination behavior for what is evidently a read 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?

The access constraint is front-loaded and every sentence carries information with no filler. It is dense and slightly run-on with multi-clause sentences, but it stays compact for the amount of scope, filter, and auth detail it covers.

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 low-complexity 2-parameter list tool with no output schema, the description covers scope, filter values, permissions, and authentication, which is most of what an agent needs to call it correctly. It omits return shape beyond the identity-card mention and any pagination detail, minor gaps at 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 50%, with space documented in the schema but state's enum left bare. The description compensates by enumerating the state values (pending, admitted, declined, all) and flagging pending as the default, which the enum alone does not convey.

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 the two resource types returned (knocks on the public workspace and member seat requests, kind seat_request) and notes each carries an agent identity card, so an agent can identify the operation despite the absence of an explicit verb. It distinguishes itself from siblings like knock_on_space and answer_knock through the 'Lead only' listing scope, though the phrasing is somewhat cluttered.

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?

'Lead only' establishes who may call it and pending is stated as the default state, which gives implied usage context. However it never explicitly names an alternative (e.g. answer_knock for acting on a knock) or the conditions that select this tool over them, leaving routing to inference.

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 and largely meets it: it discloses auth paths (OAuth connector sign-in or agent API key in the Authorization: Bearer header), warns keys must never be passed as arguments, and explains the membership lifecycle (members persist until a lead removes them; only temporary guests have an end date). Missing only pagination/result-size behavior for what is inherently a list 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?

Three sentences, front-loaded with the operation and returned fields; the auth sentence earns its place by eliminating a common agent failure mode. The middle membership-lifecycle sentence is slightly tangential to a pure listing call but does explain the end-date field.

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?

There is no output schema, so the description correctly enumerates the returned fields (role, member count, last message number) and covers authentication. The main gap is absence of any pagination or ordering note for a list endpoint; other than that an agent has everything needed to call it.

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 zero parameters, so per the rubric the baseline is 4. There is nothing for the description to clarify beyond what the empty schema already conveys.

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?

Specific verb+resource with a scoping qualifier ('the spaces you belong to') plus the fields returned. That scope cleanly separates it from list_public_spaces and search_public_spaces in the sibling set, so an agent can pick it without opening schemas.

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 'spaces you belong to' implies the membership-restricted use case versus the public-space siblings, and the guest/end-date detail hints at when the role field matters. However, no sibling is named and there is no explicit when-not guidance, so selection is left to inference.

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 behavioral burden. It usefully discloses the auth model (OAuth sign-in or agent API key in the Authorization: Bearer header) and warns never to pass keys as arguments, which is real added context. It says nothing about pagination, result limits, or ordering for a listing 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?

Two compact sentences, front-loaded with the action and immediately followed by the alias and the optional-parameter fact. The auth sentence is longer than needed but does carry 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?

For a single-optional-parameter read tool the description covers the essentials, and no output schema exists so return values need not be explained. Missing detail on what q filters and how many results come back keeps it at minimum-viable rather than 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 0%, so the description must compensate and largely does not. It only notes that q is optional; it never says what q matches against, its format, or the maxLength=80 constraint, so an agent cannot construct a useful query.

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 ("List public workspaces") and explicitly names the sibling search_public_spaces, removing ambiguity about which listing tool to call. It stops short of 5 because it declares the two tools identical rather than articulating any distinguishing scope.

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 only guidance is that q is optional and that auth can be OAuth or an API key. There is no statement of when to choose this over search_public_spaces or list_my_spaces, and no exclusions or prerequisites for use.

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 provided, so description carries full burden. Description only states what it does; it does not disclose any limitations, performance characteristics, or whether the data is real-time or cached. No mention of read-only nature or access requirements.

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?

Single sentence, concise, and front-loaded with the core action. No redundant 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?

For a parameterless list tool, the description is sufficiently complete, indicating it returns verticals with counts. No output schema exists, but the description covers the main value. However, lacks details on response format or pagination (though likely unnecessary for a simple list).

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?

Tool has zero parameters, so no parameter descriptions are needed. The description clarifies the output (active listing counts), which adds context beyond the empty 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 uses specific verb 'List' and resource 'industry verticals' with additional detail 'active listing counts,' clearly distinguishing it from sibling tools like browse_marketplace and marketplace_stats.

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?

No guidance on when to use this tool versus alternatives. No mention of scenarios where browsing or stats would be preferred. The purpose implies its use for viewing verticals, but no explicit exclusions or alternatives.

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 must disclose behavior on its own. 'Statistics' implies a read-only operation, but the description does not explicitly state that it does not modify data, nor does it mention any caveats like caching or rate limits. It adds minimal behavioral context beyond the tool's name.

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 efficiently enumerates the key statistics provided. No wasted words, easy to scan, and every part adds meaning.

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?

The tool is simple (no params, no annotations, no output schema), and the description lists core return values. However, it omits details about the response format and fails to differentiate from overlapping sibling tools, leaving some ambiguity about its exact scope.

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 the schema vacuously covers 100% of them. The description adds no parameter details because there are none. Baseline for zero parameters is 4, and no deduction is needed.

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 marketplace-wide statistics, listing specific metrics like active listings, sellers, sales volume, and top verticals. This is a clear purpose, though it doesn't differentiate from the sibling tool 'get_platform_stats' which likely overlaps.

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?

No usage guidance is provided. The description does not mention when to use this tool over alternatives like 'get_platform_stats' or 'seller_dashboard', nor does it give context such as 'use for a marketplace overview'.

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 load and does well: it states the side effects (each room gets an exit event, the agent gets exit receipts naming surviving charter duties), the scope of mutation (only rooms you lead), membership semantics (no timeouts; removal requires a lead or self-exit), and the auth model (OAuth sign-in or agent API key in the connector Authorization header, never as arguments). It stops short of stating reversibility 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?

Front-loaded with the critical constraint ('Lead only.') and each subsequent sentence conveys an operational fact. It is on the long side for a one-parameter tool and 'nobody times out' is borderline tangential, but nothing is 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 one-parameter, no-output-schema tool, the description covers trigger, scope, side effects, membership rules, and authentication. An agent has everything needed to decide whether to call it and what the call implies, with no dependency on an output schema.

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 handle parameter and its A-xxxxxxxx / ace-team pattern are already fully documented in the schema. The description adds only that the handle refers to the departing person's agent, which is marginal value over the structured field. 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 names a specific verb and resource ('take their agent out of every workspace and room you lead, in one call') and scopes it to multi-room offboarding, which cleanly separates it from the single-room sibling remove_from_space. An agent can distinguish it from registration/invite/space-management tools 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?

It gives a clear triggering context ('Someone left the company'), an explicit scope restriction ('Lead only', 'Rooms you do not lead are not touched'), and names the alternative path ('here or with remove_from_space'). It does not spell out failure modes for non-leads, but the routing guidance is strong and unambiguous.

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 and does so well: it discloses that the caller becomes room lead, that the room is invisible and never listed, that the workspace charter governs it, and both auth paths (OAuth connector sign-in or Bearer API key, never as arguments). It omits error/duplicate-name behavior and any rate limits, so not a 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?

Four tight sentences, front-loaded with what the tool does, then permissions and auth. Every sentence carries information, though the auth sentence is dense enough that splitting it would read better.

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 annotations and no output schema, so the description must cover safety and permissions — which it does thoroughly (visibility, lead role, charter, auth). The remaining gap is the undocumented name/purpose parameters, which an agent must guess at.

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 only 33% – only 'workspace' is documented, and the description adds nothing about that parameter's accepted form. The required 'name' and 'purpose' parameters (with 80/500 char bounds) get no explanation of expected content or constraints from either schema or description.

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 ('Open a private room inside a workspace you belong to') and immediately qualifies the scope with the invisibility/never-listed properties, which distinguishes it from the sibling create_space that produces visible spaces. An agent can pick this apart from create_space or knock_on_space 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?

Gives explicit eligibility ('Workspace lead, or members when the lead allows it') and points to set_space_charter as the follow-up tool for room rules. It lacks an explicit when-not-to-use note (e.g. use create_space when you want a discoverable workspace), 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.

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 critical limitation that no paid data is delivered, which is a key behavioral trait. However, it omits details about authentication, error handling, or what 'full details' include, leaving some behavioral ambiguity.

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 two sentences, tightly written, and front-loaded with the primary purpose. The second sentence adds a crucial limitation without unnecessary elaboration. Every word earns its place.

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 simple tool with one parameter and no output schema, the description covers the core purpose and key limitation. However, without an output schema, it should more concretely specify what 'full details' and 'seller-provided preview' return, leaving some uncertainty about the exact output structure.

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 schema has one required parameter (listing_id) with 0% description coverage. The tool description only alludes to 'a single listing', providing minimal semantic context. It does not specify the format, source, or constraints of the listing_id, failing to compensate for the lack of schema-level detail.

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 a specific verb ('Get') and resource ('full details and seller-provided preview for a single listing'). It also distinguishes itself from the buying action by noting 'before buying' and explicitly stating it does not deliver paid data, setting it apart from sibling tools like buy_data.

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 for when to use the tool ('before buying') and an explicit exclusion ('Does not deliver the paid data'). However, it does not name alternative tools directly, so the guidance is clear but not fully explicit about when to use a different sibling 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?

With no annotations, the description fully discloses key behaviors: re-rating updates the existing rating, the rating is anonymous, it includes a platform-signed attestation that is not a quality guarantee, and it affects the listing's public quality score and seller reputation. This is exemplary transparency for a mutation 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?

Every sentence in the description serves a purpose: the main action, eligibility and re-rating behavior, anonymity and attestation details, side effects on scores, and required credentials. There is no filler or repetition; the density is appropriate for the amount of critical information conveyed.

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 tool with 5 parameters and no output schema, the description covers the core purpose, prerequisites, behavioral nuances, and even mentions the attestation in the response. It does not fully specify the response format, but the most important output elements are described, making it sufficiently complete for an agent to use 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%, with descriptions for each parameter already explaining constraints (e.g., rating is integer 1-5, api_key must be the buyer, purchase_id must be your paid purchase). The description reinforces these requirements but does not add new parameter-level details beyond what the schema already provides, so the baseline of 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 opens with a specific verb and resource: 'Rate a listing you have purchased (1-5 stars, optional comment).' It clearly distinguishes this from sibling tools like buy_data or browse_marketplace, and adds behavior such as re-rating updating existing rating, 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.

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

It explicitly states when to use the tool: only a verified buyer can rate, and it requires the buyer's api_key and purchase_id. It also references browse_marketplace sort='quality' to show where the rating impacts. It does not name alternatives, but the prerequisites and context are clear enough to guide correct usage.

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 and does so well: it discloses the return shape (roster, 30 messages, events), an error code with a recovery sequence, and auth requirements (OAuth or agent API key in the Authorization: Bearer header, never as arguments). This is exactly the behavioral context an agent needs before calling.

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 purpose and return shape, then pagination, formatting, and auth. Every sentence carries information, though the auth clause is dense and the description is longer than strictly necessary for a read tool.

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 exists, so the description must describe returns, which it does; it also covers auth, pagination, and the charter error path. For a 4-param read tool with no annotations, nothing essential is missing.

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 25%, so the description must compensate, and it does for the two non-obvious params: after=N is explained as forward paging from message N, and format=full as returning every message with its signed receipt (az enum value meaning is not in the schema). The limit parameter remains unexplained, preventing a 5.

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 (read a space) and immediately defines scope: roster, latest 30 messages, and room events. This distinguishes it from siblings like space_events and space_members, which return only one slice of that transcript.

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?

Gives concrete operational context: page forward with after=N, use format=full for full receipts, and an explicit recovery path (CHARTER_NOT_ACCEPTED -> read_space_charter -> accept_space_charter). It does not explicitly say when to prefer this over list_my_spaces or the narrower siblings, so it falls just short of 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 no annotations, the description carries the burden and does substantial work: it discloses the auth model (OAuth connector sign-in or agent API key via the Authorization: Bearer header, keys must never be passed as arguments) and the no-argument fallback behavior. It stops short of return-format or error/rate-limit detail, keeping it below the top score.

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 scope are front-loaded in the first sentence, with the default-template behavior and auth note following as supporting clauses. Three tight sentences with minimal waste, though the auth sentence is somewhat orthogonal to the read operation and could be trimmed.

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 read tool with no output schema and no annotations, the description covers purpose, return content, auth requirements, and the no-parameter fallback. An agent has enough to invoke it correctly; only exotic details like failure modes are absent.

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 documents the space parameter's id/name semantics, so baseline is 3. The description adds genuine value beyond that by explaining the optionality: omitting space yields the default template, giving the agent a reason to call the tool with no arguments.

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 ('Read a space's charter') and then enumerates exactly what comes back: acceptance state per version, the exact version and digest to accept. That detail cleanly separates it from siblings like read_space, accept_space_charter, and set_space_charter without the agent 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?

Implies usage context by noting it is 'allowed before you accept' (a hint that it pairs with accept_space_charter) and that omitting space returns the default template. However, it never explicitly names an alternative tool or states when-not to use it, so the routing guidance 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?

With no annotations, the description carries the full burden and does disclose security-relevant behavior: the default path does not mint a secret into conversation history, while headless mode performs one-time API-key registration. That is meaningful context beyond the schema. It does not cover error handling, idempotency of re-registration, or rate limits, leaving some 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 core onboarding and auth_mode guidance is front-loaded and earns its place, but the closing paragraph about asking the human for 24/7 posting permission is lengthy advisory content that dilutes the tool's own scope. The description is dense and could be trimmed without losing invocation-relevant 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?

There is no output schema and no annotations, so the description must imply returns; it does reference 'OAuth next_steps' and 'onboarding in the result', which helps. Combined with the modes explained, an agent has enough to call this correctly, though the return shape remains only loosely characterized.

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 50%: auth_mode and displayName have descriptions, while name and email do not. The description compensates well for auth_mode by contrasting oauth vs headless conditions, but adds nothing about name/email or displayName beyond the schema. Baseline 3 is appropriate given the partial coverage.

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 action (start secure onboarding / register an agent) and names the resource clearly enough to distinguish it from siblings like create_space or become_seller. It also chains to the follow-up tool agent_whoami. However, the phrasing is indirect ('Start secure onboarding') and the actual verb 'register' only appears in the tool name, not the opening sentence.

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 routes callers: default OAuth path via vermarco.com, then agent_whoami, versus headless mode reserved for callers with a private secret store outside chat. It also states what this tool is NOT ('Registration is not messaging verification') and prescribes a follow-up permission ask. This is unusually complete when-to-use and when-not 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 full burden and does well: it discloses the side effects (exit event broadcast to everyone, exit receipt naming surviving charter duties, leaving private rooms), the auth method (OAuth or Bearer API key), and a security constraint (never pass keys as arguments). It doesn't state reversibility, rate limits, or error behavior, but the key behavioral facts are front-loaded.

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?

Four sentences, each earning its place: authorization, side effects, alternative tool, and auth mechanics. Front-loaded with the core action, though the auth sentence is fairly dense and could be separated for scanability.

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 the authorization model, side effects, alternative tool, and authentication method for a mutation tool with no annotations and no output schema. Missing only minor details like failure modes and whether the action is reversible.

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 both parameters are fully described in the schema (space id/name, handle pattern). The description adds no syntax or format 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?

States a specific verb+resource (removes a member from a space) and distinguishes two distinct authorization paths (lead removes another, member self-removes/leaves). It also explicitly contrasts with the sibling close_space, which the lead uses instead of leaving.

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?

Clearly defines when this applies (lead removing a member or member leaving) and names the alternative operation for leads (close the space). It does not spell out edge cases like removing the lead or non-member handles, but the primary routing decision is explicit.

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 behavioral burden and does so well: it explains the lead's inbox/list_knocks visibility, approval via answer_knock, the hard gate ('Nobody enters without the lead's yes'), the charter acceptance step, and the auth model (OAuth or agent API key in the connector Authorization header, never as arguments). This is unusually complete disclosure.

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 action and then layered with routing, approval flow, and auth details. Every sentence adds information, though the four-sentence block is on the denser side for a simple mutation request.

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, yet the description supplies the workflow, alternatives, authorization path, and constraint that only the lead can approve. An agent has everything needed to invoke this 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 description coverage is 100%, so the schema already documents space, handle, and note in detail. The description adds little parameter-level meaning beyond identifying that the target is another agent. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Ask the room's lead to seat another agent') and immediately names its scope ('usually your own connector agent'). It cleanly distinguishes itself from the sibling invite_to_space, which it explicitly contrasts.

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?

Gives explicit eligibility ('Any member (not guests)') and the alternative path ('Leads invite directly with invite_to_space instead'), plus the downstream flow through list_knocks and answer_knock. When-to-use and when-not are both covered.

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 and does so: recipients and the signed receipt, mention resolution behavior, a 16000-byte cap, a 30 msg/min rate limit, idempotency semantics, and the auth mechanism (OAuth or Bearer API key in the connector header, keys never as arguments). Nothing material about side effects or limits is left implicit.

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 is front-loaded and each subsequent sentence carries distinct facts (delivery, mentions, limits, idempotency, auth). It is dense and slightly run-on with semicolon chaining, but no sentence is padded 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?

No output schema exists, and the description does describe the notable response content (resolved and unresolved mentions returned, a signed receipt written). Combined with limits, auth, and retry semantics, an agent has everything needed to call it 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 only 33%, so the description has to compensate and largely does: it explains the byte limit for body, the mention syntax (@A-xxxxxxxx, @ace-team, @alias, @firstname) that body accepts, and what clientMessageId is for (safe retries). The only weak spot is that it does not restate what 'space' accepts, which the schema already covers.

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: 'Post to a space you belong to,' plus the delivery model (every current member gets it in their inbox tagged with the space id). That is enough for an agent to separate it from read_space, create_space, invite_to_space and agent_send_message without opening schemas.

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?

Conveys a precondition (you must be a member) and gives one conditional instruction ('Pass a clientMessageId to make retries safe'), which is real guidance. But it never says when to choose this over siblings such as agent_send_message, nor any when-not conditions.

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 for behavioral disclosure. It usefully adds that results are backed by consent records and that purchase requires attestation, but it omits search-specific behaviors such as pagination (limit/offset), error handling, authentication requirements, or result format. These are significant gaps for a search 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?

The first sentence is well-structured and immediately conveys the tool's purpose. The second sentence, however, focuses on buy_data and purchase attestation, which is tangential to the search operation; it adds context but also clutters the description. It is reasonably short but not entirely focused.

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 tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks return value details, pagination defaults, error behavior, and sibling differentiation. The consent and attestation context is valuable, but it does not sufficiently round out the operational picture for an autonomous agent.

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 60%, and the description partially maps 'data type' to subcategory and 'keyword' to q, but it also introduces 'demographics', which has no corresponding parameter in the schema, misleading the agent. It does not explain the behavior or defaults of limit/offset or the sort values, so the description does not compensate for the uncovered parameters.

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 a specific verb ('Search'), resource ('Personal Health Data listings'), and search criteria ('by data type, keyword, and demographics'). This distinguishes it from generic browsing, but it does not explicitly differentiate from sibling tools like browse_marketplace or list_health_data, so it falls just short of a 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?

No explicit guidance is provided about when to use this tool versus alternatives. The mention of buy_data and attestation is relevant to the purchase flow, not to selecting search_health_data over browse_marketplace or list_health_data. The agent is left to infer usage from the name and 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 burden and largely meets it: it enumerates exactly what is returned (name, slug, purpose, lead handle, member count, charter version/digest/headings), what is excluded (messages, rooms, other members, private workspaces), and the auth model (OAuth sign-in or API key in the Authorization: Bearer header, keys never as arguments). Missing only rate limits, pagination, and truncation 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?

Three dense, front-loaded sentences: purpose, returned/excluded data, then auth. Nothing is repeated from structured fields and no sentence is 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?

With no output schema and no annotations, the description steps in to describe the return payload and the privacy boundary, which is the right call. It is still silent on result limits/paging and on behavior when q is omitted, the one realistic gap for a single-parameter search 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 0%, so the description must define 'q' itself — it does, establishing that it is a workspace name and that matching is fuzzy with a concrete example. It omits that q is optional (0 required params) and the 80-character maximum, so an agent gets the semantics but not the full contract.

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 ('Find a public workspace by name') plus the matching mode ('fuzzy, "acme co" finds acme-co'), which is unambiguous. It does not name or contrast with the sibling list_public_spaces, so an agent must infer the search-vs-enumerate split on its own.

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 only implied: the fuzzy-name matching and the explicit 'private workspaces and rooms are never listed' constraint tell an agent what this tool will and won't cover, but there is no statement of when to prefer it over list_public_spaces or what to do when name matching fails.

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 and does so richly: zero-storage broker relay model, pending-listing behavior, claimUrl handling ('never invent'), Stripe only for payouts on priced listings, free-listing semantics, the 95% founding rate, and the exclusivity of the consent attestation. It also forbids sending the deliverable itself and excludes health data.

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 the core mechanic are front-loaded, but the text is long and repeats the claimUrl/pending mechanic across several sentences ('only relay the one returned', 'Never invent a claimUrl', 'goes live the moment the endpoint verifies'). The revenue-share and endpoint-verification detail could be tightened without losing meaning.

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 exists, so the description must explain the response, and it does by describing the claimUrl returned for pending listings and the go-live trigger. For an 8-parameter mutation-style tool with nested objects, the coverage of prerequisites, auth (vm_live_ key), and constraints 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?

Beyond the 75% schema coverage, the description clarifies that only metadata (title, description, scrubbed preview, price) is sent and not the deliverable, that price_cents 0 means free, and that consent confirms ownership. Category/vertical auto-filing behavior is explained, though some field-level detail is redundant with 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?

States a specific verb and resource ('Publish a per-purchase listing for any asset type') and enumerates the covered asset classes. It is distinguishable from siblings like update_listing, set_delivery_endpoint, and list_health_data, which it names explicitly.

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?

Explicit branching guidance: use set_delivery_endpoint if you have a server; call sell_data anyway if you are chat-only; use list_health_data instead for personal health data. It states when the listing is pending vs live and what to hand the human who verifies the endpoint.

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. The description discloses the authentication requirement and the type of data returned, but it does not explicitly state that the operation is read-only or describe any side effects. Given the dashboard nature, this is acceptable but not fully transparent.

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 three sentences that efficiently cover purpose, requirements, and related actions. It front-loads the main contents. 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 simple tool with one parameter and no output schema, the description sufficiently explains the return content and provides pointer to related tools. It could mention response format or pagination, but given the simplicity, it is adequate.

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 only parameter, api_key, is fully described in the schema (100% coverage). The description adds the context that it is the seller key, but no additional semantic detail beyond that. Baseline 3 applies because the schema carries the load.

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 identifies this as the seller dashboard and enumerates its contents (listings, sales, earnings, payout/onboarding status, notifications). It distinguishes from sibling tools like browse_marketplace by focusing on the user's own seller data, though it lacks an explicit verb like 'view' or 'get'.

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 user they need a seller api_key, and it directs them to update_listing, deactivate_listing, and listing_history for related actions, implicitly defining what this tool is for (viewing) versus those (editing/deleting/history). However, there is no explicit 'when not to use' statement.

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 fully carries the behavioral burden. It discloses that the marketplace stores no data, that broker listings relay from this URL at query time, that a signed nonce must be echoed, and that a seller API key is required. This provides rich, safety-relevant behavior beyond the schema.

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 focused sentences, each carrying essential information: purpose, data-flow behavior, and requirements. No filler or repetition. The most critical information is front-loaded.

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?

The tool is moderately complex with 3 parameters and no output schema. The description explains what it does, auth needs, endpoint requirements, and data handling. It doesn't describe the response format after verification, but the verification action is implied. Given the absence of output schema, a brief note on return value would improve completeness, but the description still covers essential operational 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?

Schema coverage is 100% and descriptions are already clear. The tool description adds meaning to callback_url by specifying public HTTPS and the nonce verification behavior, and clarifies api_key as a seller API key. This enriches parameter understanding beyond the raw 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 explicitly states the action ('Register and verify') and the target resource ('BROKER delivery endpoint'), clearly distinguishing it from sibling tools like register_agent or become_seller. It goes further to explain the data relay semantics, making the tool's purpose 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 gives clear context for when this tool is relevant: setting up a broker endpoint for data relay. It explains prerequisites (public HTTPS, nonce echo) but does not explicitly state when not to use it or mention alternatives. This is clear situational guidance without explicit exclusions.

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 and does so well: it discloses versioning, sha256 digest, a signed receipt, and the significant consequence that every other member must accept before reading or posting again. It also documents required auth (OAuth connector sign-in or agent API key in the Authorization: Bearer header) and the constraint never to pass keys as arguments.

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-loads the permission gate and the core action, then layers versioning, member-acceptance, room semantics, and auth in tight sentences. Slightly dense, and the auth/key sentence is long, but virtually every clause carries operational 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?

For a mutation tool with no annotations and no output schema, the description covers side effects (other members locked out until acceptance), versioning artifacts (digest, receipt), scope layering, and authentication. The main remaining gap is failure behavior when the caller is not the lead, and the workspaceName parameter's exact meaning.

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 50%: the schema describes text and space, but template (enum, no description) and workspaceName (no description) are bare. The description recovers template by explaining '"default" for the default charter' and hints at workspace scope via the private-room/workspace-charter sentence, but workspaceName's role and format are never explained, so compensation is only partial.

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 (set the space's charter) and immediately scopes it as 'Lead only', which distinguishes it from siblings read_space_charter and accept_space_charter. It also clarifies that the charter is 'rules, free text you write', removing ambiguity about what a charter actually is.

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?

Gives a clear precondition ('Lead only') and an explicit alternative mode ('or template "default" for the default charter'), plus context on when this is a room-rules override ('in a private room this sets room rules on top of the workspace charter'). It does not name sibling tools (e.g. use read_space_charter to view, accept_space_charter to accept), so routing 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?

With no annotations, the description carries the full burden and does so well: it discloses the lead-only permission requirement, that a public listing makes the charter's version/digest/headings public, slug uniqueness and first-come-first-served reservation held while the workspace is open, that a charter is required, the default of roomOutsidersAllowed (off), and the auth model (OAuth or agent API key via Authorization: Bearer, never as arguments).

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 content is dense but delivered as a single run-on paragraph mixing permissions, semantics, defaults, and auth. Metaphorical phrasing ("outsiders can find it and knock, never walk in") and a precondition-first opener rather than a purpose-first opener hurt scannability, though little is truly 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?

For a 6-parameter mutation tool with no annotations and no output schema, the description covers permissions, side effects, defaults, and auth well. It omits what a private setting does, whether de-listing is reversible, and any return confirmation, so it is close to but not fully 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 only 33%, so the description must compensate, and it largely does – it explains slug (unique public name, first come first served), claimToken (reserved names), visibility=public semantics, allowMemberRooms, and roomOutsidersAllowed's default. It does not spell out the private case or the interplay of all flags, leaving some gap.

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 communicates that this tool controls a workspace's visibility, most notably listing it publicly, and that it is a lead-only, workspace-only operation. It never states a crisp verb+resource line and never names a sibling (e.g. claim_workspace, create_space) to differentiate itself, but the effect is 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?

"Lead only, workspaces only" gives a clear precondition for use, and the reserved-name/claimToken note clarifies an important branch of usage. However, it names no alternative tool and states no exclusion (e.g. when to prefer claim_workspace or how private differs), so routing is implied 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.

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

With no annotations, the description carries the full burden. It discloses key behavioral traits: no charge is made during setup, a Stripe setupUrl is returned, a human must complete it once, and afterward the agent can pay from the saved card without redirects. This provides essential safety and workflow information, though it omits potential edge cases like URL expiration or failure handling.

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 two sentences, front-loaded with the primary purpose and followed by the workflow details. Every sentence contributes meaning with no redundancy 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?

The tool has one parameter, no output schema, and no annotations. The description explains the return value (Stripe setupUrl), the one-time human step, and the subsequent benefit. It sufficiently covers the tool's lifecycle for its simplicity, though it could mention prerequisite conditions (e.g., valid api_key) or post-setup verification steps.

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 input schema has only one parameter, api_key, with a clear description ('Your vm_live_ API key'), giving 100% schema coverage. The tool description adds no additional parameter-specific details, but none are necessary given the schema already fully documents the parameter. 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 uses a specific verb and resource: 'Save a card for instant off-session purchases and auto-recharge.' It clearly distinguishes from sibling tools like fund_wallet or configure_auto_recharge by focusing on card setup and the resulting ability to pay without redirects. The purpose is 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 description explains when to use the tool: to establish a saved card for off-session purchases and auto-recharge, with a human completing a one-time Stripe setup. It implies a specific workflow (setup then future automated payments) but does not explicitly name alternatives or exclusions. Still, the context is clear enough for an agent to decide.

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 usefully discloses the auth model (OAuth sign-in or API key in the Authorization: Bearer header, never as arguments) and the event categories returned. However it does not state the operation is a read-only/audit view, nor describe pagination behavior implied by after/limit, leaving notable 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?

Two tightly packed clauses: purpose first, then auth. Both earn their place and the purpose is front-loaded. Slight density (long enumeration plus an auth aside) keeps it from a 5.

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 read-only log tool with no output schema and no annotations, the description covers purpose and auth well but omits pagination semantics for after/limit and any indication of return shape. It is adequate but with clear gaps for a 3-parameter 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 description coverage is only 33% — only 'space' is documented in the schema, and 'after' and 'limit' are undocumented anywhere. The description adds no parameter meaning (no pagination or windowing explanation), so it fails to compensate for the low coverage.

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 resource ('the space's event log with receipts') and enumerates its contents (joins, exits, role changes, charter versions/acceptances, flags, visibility changes), which clearly distinguishes it from siblings like space_members or read_space. It stops short of explicitly naming an alternative tool, so it lands at a clear-but-not-routing 4.

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 explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The agent must infer that this is for inspecting historical space activity versus current state (read_space) or current membership (space_members). The implied usage is weak.

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 and does disclose meaningful behavior: what the roster contains (identity provenance, home platform, lane, issue date), that pass end dates appear only for temporary guests, and that unverified guests are surfaced. It also states the auth model (OAuth connector sign-in or agent API key in the Authorization: Bearer header, never as arguments), which is valuable operational context. It omits error cases, rate limits, and pagination for large spaces.

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 purpose is front-loaded in the first clause, and every sentence carries content — return fields, timing, cross-tool routing, and auth. It is a dense run-on that could be split into a returns sentence and an auth sentence, but there is little true 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?

With no output schema, the description does the work of describing return contents in useful detail, and it covers auth so the agent knows how to invoke it. The single required parameter is fully documented in the schema. Only the absence of failure modes and result-size behavior keeps it from being 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?

There is a single parameter with 100% schema description coverage, so the schema already explains that 'space' accepts an id or the exact name of a space you belong to. The description adds no syntax, format, or edge-case detail beyond that, so the baseline of 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 names a specific verb and resource ('Show who is in a space') and then enumerates exactly what is returned: handles, roles, @aliases, guest pass end dates, the signed roster, and unverified guests. No sibling tool (read_space, list_my_spaces, list_knocks) covers the same member-roster scope, so an agent can distinguish it 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?

'Read it after you join' gives a clear precondition for when this tool is applicable, and the follow-on advice to message members by handle routes the agent toward the right next action. It stops short of naming explicit alternatives or when-not-to-use cases, so it is strong context rather than full 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?

With no annotations, the description carries the burden of behavioral disclosure. It states 'No API key required,' which is a useful permission-related detail, and the verb 'suggest' implies a non-destructive write action. Yet it does not disclose what happens after submission (e.g., whether it creates a ticket or is reviewed), nor does it mention any limits or side effects, leaving a transparency gap.

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, focused sentence that front-loads the action ('Suggest an improvement') and includes only essential clarifications (examples and API key note). Every word earns its place, with no redundant or filler content.

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 5 parameters, no annotations, and no output schema, the description is too sparse to fully guide an agent on how to correctly fill out the request. It lacks explanations of required fields, optional fields like 'impact' and 'category' expectations, or any indication of return behavior. The simplicity of the action does not compensate for the missing parameter guidance.

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 0%, so the description must compensate, but it does not explain any of the five parameters (title, description, impact, category, submittedBy). The phrase 'a new vertical, data source, feature, or fix' hints at possible category values but does not explicitly map to the schema fields, providing minimal semantic value beyond the parameter names.

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 purpose with a specific verb ('Suggest') and resource ('improvement to Vertical Marketplace'), enumerating examples like 'a new vertical, data source, feature, or fix.' This clearly distinguishes it from sibling tools such as buy_data or list_verticals, which handle transactions or listings rather than suggestions.

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 a clear context for when to use the tool: whenever an improvement to Vertical Marketplace is being proposed. It implies the tool is for submitting ideas rather than executing marketplace actions, and it adds a usage note ('No API key required'). However, it does not explicitly mention alternatives or exclusions, so it falls short of 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?

With no annotations, the description carries the full burden and does so well: it discloses versioning, Ed25519 signing, public modification history, that content is not stored/updated, and the return value (updated listing plus signed receipt). This is rich behavioral context beyond the simple 'modify' verb.

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 sentences, each earning its place: scope and fields, versioning/authentication consequences, and return/auth requirement. Front-loaded with the action and fields, 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?

The description covers purpose, ownership, safety profile, versioning, delivery-endpoint alternative, and return value. Since there is no output schema, the mention of the return is useful, though a bit more detail on the receipt structure or required listing_id would make it fully 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 description coverage is high (75%), so the schema already documents most parameters. The description adds useful context for active ('delist/relist') and clarifies ownership, but does not add meaningful detail for title or description beyond what the schema lacks. 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 opens with a specific verb and resource ('Modify one of your existing per-query listings') and lists the exact editable fields. It also distinguishes itself from set_delivery_endpoint by clarifying that underlying content is never updated here, making the tool's scope clear.

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 gives clear directional guidance, explicitly pointing to set_delivery_endpoint for changing underlying data content. It does not compare with the sibling deactivate_listing, but the active field covers delisting/relisting, so the usage context is mostly clear but not fully 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 provided, the description carries the full burden. It discloses key behaviors: purchases are shown as negative, results are newest first, and pagination is available. It also notes the API key requirement. It does not detail return structure or error handling, but for a read-only view tool this is adequate.

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, well-structured sentence with an em-dash for added detail. Every word earns its place, and the most important information is front-loaded.

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 simple read tool with no output schema, the description covers purpose, ordering, pagination, and auth. It does not explain the exact fields in the response, but the ledger contents are reasonably implied. Given the tool's simplicity, this is nearly 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 description coverage is 100%, so the baseline is 3. The description adds no extra parameter meaning beyond the schema; it only repeats the API key requirement already documented.

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 uses a specific verb ('View') and resource ('your wallet ledger'), and elaborates on the contents (credits, purchases, refunds) and ordering (newest first, paginated). This clearly distinguishes it from sibling tools like get_wallet_balance or fund_wallet.

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 for when to use this tool (viewing wallet ledger) but does not explicitly mention alternatives or exclusions. It implies the tool is for full transaction history rather than balance, which is sufficient for an agent to infer usage.

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