PeerPush

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

Annotations already cover safety (readOnlyHint=true, destructiveHint=false, openWorldHint=false), yet the description still adds real value: the shape of the comparison returned and, importantly, the partial-result edge case where products known only as alternatives come back under notListedOnPeerPush with name and website. That failure-mode disclosure is exactly what annotations cannot express.

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 usage, then return shape, then the edge case. Every sentence carries information, though the closing linking advice (websiteUrl vs peerpushUrl) is slightly tacked on and could be folded into the return description.

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 carry return semantics, and it does: shared/unique features, pricing differences, platform coverage, use cases, audiences, community metrics, plus the notListedOnPeerPush fallback. An agent has everything needed to call and interpret this 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?

Only one parameter with 100% schema coverage, so the schema already documents the array, minItems=2, maxItems=5, and the example. The description restates '2-5 named software products' and adds that products are matched by name, which is marginal over 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?

Specific verb ('Compares') plus resource and cardinality ('2-5 named software products side by side'). This clearly separates it from siblings like peerpush_find_alternative and peerpush_product_details, which handle single-product or alternative lookups.

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?

States the triggering intent explicitly: comparison requests or 'which of several specific products to choose', with the example 'Vercel vs Netlify'. It implies rather than states the exclusion (use peerpush_find_alternative when you don't have named products), so it stops short of full when/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?

Beyond the annotations, it discloses the no-auth requirement, non-idempotent behavior ('Each successful call creates a new product'), the no-retry caution after uncertain responses, privacy instruction for the claim link, and the fact that nothing is claimed/published/purchased. This is 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 compact, front-loaded with the core purpose, and every sentence adds necessary operational information: auth, endpoint parity, return value, user interaction, exclusions, and retry guidance. 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?

The definition is unusually complete for a mutation: it covers auth, side effects, output envelope, user-handling steps, and failure/retry guidance. It falls slightly short only in not compensating for the minimal schema coverage of the many input fields, though the endpoint-parity reference partially mitigates that.

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 4%, so the description bears a heavy responsibility to explain 24 parameters, but it only refers generically to 'the same fields as POST /api/v1/products' without explaining any parameter semantics. The output fields are listed, but no meaning is added for inputs like mrr, alternatives, discountCodes, or how to populate required 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?

The description opens with a specific verb and resource—'Create a private, unclaimed product on PeerPush'—and clarifies the object's state (private, unclaimed). It also distinguishes itself by describing the return envelope with claimUrl, which none of the read/discovery sibling tools would produce.

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 the trigger condition: 'Only create when the user asks to create a product.' It also gives when-not context by noting the tool 'does not claim, publish, or purchase anything,' but it does not name sibling alternatives or describe when a discovery tool should be used instead.

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

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the description's burden is lighter. It adds real value beyond them by disclosing the behavioral filter ('currently active discount codes') and the return content (discount code and percentage off), which matters since there is no output schema. It stops short of any pagination or result-ordering 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?

Three short sentences, front-loaded with the core purpose, and every sentence carries distinct information (purpose, trigger, return shape, linking guidance). Minor redundancy between 'currently active discount codes' and 'their active discount code' 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?

With no output schema, the description correctly compensates by naming the returned fields (discount code, percentage off) and telling the agent how to link results via websiteUrl or peerpushUrl. Combined with annotations covering safety and a fully documented 2-param schema, 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?

Schema description coverage is 100%, so both parameters (limit, category) are already documented, making 3 the baseline. The description adds no meaning beyond the schema for either parameter — the websiteUrl/peerpushUrl sentence concerns returned fields, not inputs.

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 (Lists) plus resource (products on PeerPush) narrowed by a concrete condition (currently active discount codes), which cleanly separates it from siblings like peerpush_trending, peerpush_new_launches, and peerpush_find_product. An agent can route a deals/discounts/coupons request without opening any schema.

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

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

Explicitly gives the trigger context: 'Relevant when the user asks about software deals, discounts, coupons, or promotions.' That is a clear when-to-use signal, but it names no alternative tool and gives no when-not condition (e.g., how it differs from peerpush_trending when a trending product also has a discount).

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

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

Annotations already establish the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the description only needs to add operational context. It does: results are sorted by score/recency/trending momentum, and each product should be linked via websiteUrl or peerpushUrl. It does not say how filters combine or how many results are returned, but the added return-handling guidance is genuine value beyond the annotations.

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 doing distinct work: purpose, routing condition with example, and return/linking guidance. The scoping contrast is front-loaded. Slightly dense in the first sentence's criteria list, but nothing is padding.

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

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

With 7 optional parameters, no output schema, and annotations covering safety, the description covers what an agent needs: what it returns, how it is sorted, and how to present links. The remaining gap is filter combination semantics (AND vs OR) and result limits, though limit/max is documented in the 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 all seven parameters are already documented in the schema, making 3 the baseline. The description mirrors the schema's dimensions (use case, audience, platform, pricing, category) and glosses "trending" as "trending momentum," but adds no syntax, combination, or matching rules beyond what the schema 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 states a specific verb and resource ("Browses the PeerPush catalog") and immediately scopes it to structured criteria (use case, audience, platform, pricing, category). It contrasts itself against keyword search, which is what the sibling finder tool does, so an agent can route correctly without opening either schema.

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

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

It gives an explicit when-to-use condition ("the user wants to explore products matching specific filters rather than a keyword search") plus a concrete example query. It stops short of naming the sibling tools it competes with (peerpush_find_product, peerpush_trending, peerpush_new_launches) or stating when filters are the wrong choice.

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

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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds real value beyond them by disclosing the return shape (ranked alternatives with pricing, platforms, use cases, community engagement metrics) and a linking instruction to websiteUrl or peerpushUrl — meaningful since no output schema exists.

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 purpose before the usage trigger and return/linking detail. Every sentence carries information; only the linking sentence is marginally operational rather than definitional.

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

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

With no output schema, the description compensates by summarizing return contents and link targets, and the read-only annotations cover the safety profile. Filtering behavior (audience, platform, pricing) is left to the schema, which documents it fully, so 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 description coverage is 100%, so all five parameters (limit, product, audience, platforms, pricingType) are already documented in the schema with examples and enum values. The description's mention of pricing and platforms only echoes returned fields rather than adding new parameter semantics, 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 ('finds') and resource ('alternatives and competitors to a named software product'), which is clearly distinct from sibling lookup tools like peerpush_find_product or peerpush_product_details. However, it never names a sibling to sharpen the boundary, so it stops 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?

Gives an explicit triggering condition ('when the user asks for an alternative, replacement, or competitor to a specific product') with concrete example phrasings such as "alternative to Notion" and "something like Figma but free". No when-not guidance or named alternative tool is offered.

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

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

Annotations already declare the read-only, non-destructive, closed-world profile, so the safety burden is covered. The description adds real context beyond that: results are ranked by relevance and community engagement, and products should be linked via websiteUrl or peerpushUrl. It does not mention result caps beyond the schema's limit, pagination, or empty-result behaviour.

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: purpose and mechanism, when it applies, and what comes back plus how to present it. The most decision-relevant information (search + semantic matching) is front-loaded 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?

With no output schema, the description takes on the burden of describing returns, and it does so at a high level (ranked by relevance and community engagement, with URLs for linking). Combined with a fully documented 8-param schema and complete annotations, an agent has what it needs to call this correctly; only edge-case behaviour is unstated.

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

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

Schema description coverage is 100% and every parameter (query, limit, sort, useCase, audience, category, platforms, pricingType) is already documented with examples and enums in the schema. The description only summarises the filter families ('pricing, platform, audience, and use case') without adding syntax, defaults, or interaction rules. Baseline 3 is appropriate since the schema carries the 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?

States a specific verb and resource ('Searches the PeerPush product catalog') and explains the mechanism (natural language query plus semantic matching with optional structured filters). The example query and the recommendation intent make the tool's job unmistakable. It stops short of naming near-neighbours like peerpush_discover or peerpush_find_alternative, so an agent must infer the boundary.

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 triggering condition: 'Relevant when the user wants a software product, tool, app, or service recommended for a specific need.' That is enough context to select it over generic search. There is no explicit when-not guidance or pointer to peerpush_find_alternative / peerpush_compare for the adjacent intents.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only a light behavioral note ("Returns the most recently published products") and no pagination, result-count, or ordering semantics, which is the minimum-plus for a tool whose annotations already carry the safety burden.

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

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

Three short sentences with the purpose front-loaded and zero filler. The closing linking advice is slightly output-oriented but useful and compact; nothing is 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?

With no output schema, the description carries return-value burden and does mention the key URL fields (websiteUrl, peerpushUrl) an agent should surface. It leaves ordering and result-shape details thin, but the schema fully covers inputs and annotations cover safety, so an agent can call 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 days, limit, and category are already documented with defaults and bounds in the schema. The description alludes to the days window but adds no meaning beyond it, 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 ("Lists products recently launched on PeerPush") plus a scope constraint ("within a chosen number of days"). It is clearly differentiated in kind from mutation siblings like peerpush_create_product, though it does not explicitly contrast with the closest read siblings such as peerpush_trending or peerpush_discover.

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 an explicit trigger condition: "Relevant when the user asks about newly launched products or recent software releases." That is clear when-to-use context, but it names no alternatives or exclusions, so an agent must still infer why this beats peerpush_trending or peerpush_deals.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds useful value beyond that by enumerating the returned payload (pricing, discount codes, community metrics, development updates, alternatives) and by prescribing how to link the result via websiteUrl or peerpushUrl.

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 before the usage triggers and return details. Each sentence carries information, though the return-value enumeration is somewhat list-heavy relative to the space available.

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 appropriately compensates by describing the return contents, and it supplies the linking guidance an agent needs to cite the product. For a two-parameter read tool with annotations covering the safety profile, 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% and both parameters are already documented, so the schema does the heavy lifting. The description adds no syntax or format guidance for 'product' beyond what the schema states, and only loosely references the alternatives flag.

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 ('Looks up a single product on PeerPush by name or slug'), which is clear and actionable. It does not, however, distinguish itself from the nearby peerpush_find_product sibling, leaving the agent to infer the difference between the two lookup 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?

Gives clear usage triggers ('Relevant when the user asks about a specific product's pricing, features, platforms, target audience, or recent activity'). It stops short of naming when NOT to use it or pointing to alternatives such as peerpush_find_product or peerpush_compare for multi-product needs.

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

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

Annotations already establish readOnly/non-destructive/non-open-world, so the description is freed to add content-level behavior: trending badges, rising upvotes, and Product of the Day/Week/Month award winners, plus the linking guidance for websiteUrl vs peerpushUrl. It does not cover pagination or how trends are computed, but it adds real context beyond the annotations.

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 scope, then usage trigger, then return/linking detail. Slight looseness in the 'popular, hot, or gaining momentum right now' triple, but nothing is off-topic or 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?

No output schema exists, so the description carries the return-value burden, and it does so at a reasonable level (trending badges, upvotes, award winners, URL fields). It stops short of describing result ordering or response shape, which leaves a small gap for a list tool with no 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 limit, period, and category are all documented in the schema; the baseline is 3. The description restates the period options ('day, week, or month') but adds no new semantics such as what 'category' accepts beyond the schema's own example, so it neither compensates nor detracts.

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 ('Lists') plus a precise resource ('software products currently trending on PeerPush') and the scoping dimension (day/week/month). It implicitly separates itself from time-oriented siblings like peerpush_new_launches by emphasizing current momentum, but it never names a sibling explicitly, which keeps it 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 second sentence gives a clear trigger condition: 'when the user asks what tools are popular, hot, or gaining momentum right now.' That is a usable when-to-use signal, but there are no exclusions or named alternatives (e.g. use peerpush_new_launches for brand-new releases, peerpush_deals for discounts).

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