Vibe Manufacturing

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

Annotations only declare readOnly=false, idempotent=false, destructive=false, so the description carries most of the burden and does add real value: it discloses an external side effect (emails are sent to opted-in manufacturers), the consent precondition, and the return payload (contact, quote-form and agent links, RFQ id, token). It does not warn that re-calling creates duplicate RFQs and duplicate emails, which matters given idempotentHint=false.

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, no filler, and the outcome is front-loaded before the consent constraint. Slightly dense clauses ('direct contact, quote-form and agent links for all matches plus an RFQ id and a token') cost it the top mark.

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 usefully explains what is returned (links, RFQ id, token), which is a real contribution. But for a 15-parameter, non-idempotent creation tool with 20% schema coverage, the missing parameter guidance and duplicate-submission warning leave an agent under-informed.

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% across 15 parameters, and the description compensates with nothing about the inputs — it only enumerates return values (links, RFQ id, token). Key inputs such as process, quantity, materials, cad_files, needed_by, tolerance_mm, certifications and ship_to_country are undocumented in both places.

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 ('Create a structured request for quotation') and explains the downstream behavior (matching manufacturers, emailing opted-in ones, returning links plus RFQ id and token), which differentiates it from read-oriented siblings like get_rfq. However, it never distinguishes itself from the near-identical sibling submit_quote_request, so an agent cannot route between the two from the description alone.

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 an explicit precondition: 'Only call after the user agreed that the request is shared with matched manufacturers,' which is a genuine gating rule rather than vague advice. It stops short of naming alternatives (e.g., find_suppliers, match_manufacturers, submit_quote_request) or stating when not 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?

readOnlyHint=true is consistent with an estimate/calculation tool, and the description reinforces this by framing the output as an estimate rather than a commitment. It adds the useful constraint that all money values are USD per unit, but says nothing about default behavior for the 10 optional inputs, precision, or the response shape.

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 with the primary output (landed cost) front-loaded and the currency/unit convention stated immediately after. Nothing is wasted, though the brevity is partly under-specification rather than pure efficiency.

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?

A 10-parameter, 0%-covered calculator with zero required fields and no output schema leaves the agent unable to know what defaults apply, how labor is derived from assembly_minutes times labor_rate_per_hour, or what the returned estimate contains. The description should do far more given 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 0% across 10 parameters, so the description carries the full burden and does not meet it. It clarifies that money inputs are USD per unit, but leaves the units of assembly_minutes, the meaning of returns_percent vs payment_fee_percent vs target_margin_percent, and which inputs are optional (0 required) entirely unexplained.

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 ('Estimate') with two concrete outputs: landed cost per unit and the price needed to hit a target margin. The domain (custom product costing) is clearly distinct from the RFQ/quote/supplier siblings, though it never names or contrasts them 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?

No when-to-use guidance, no prerequisites, and no routing relative to siblings like submit_quote or get_rfq. The agent must infer that this is a standalone pricing calculator rather than a procurement action.

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, so the safe-read profile is covered. The description adds no return-shape, pagination, default-limit, or no-filter behavior context, so with annotations carrying the safety burden a 3 is appropriate.

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 in the first clause, followed by the two parameter hints. The long process enumeration is dense but each item earns its place as the only enumeration of valid values; still, a single unwieldy sentence is slightly less scannable than it could be.

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 return values need not be explained. However, with zero required parameters the description should say what happens when called with no filters (return everything? cap at limit?) and whether limit has a default, which it does not.

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

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

With 75% schema coverage, the schema already documents limit and country format. The description genuinely adds value by enumerating all valid process ids (laser-cutting, cnc-machining, etc.), which the schema lacks as an enum, and restates the accepted country formats. It is silent on the city parameter, keeping it below 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+resource+scope: 'Find contract manufacturers in the directory by country and process.' An agent knows exactly what it returns. It does not, however, explicitly distinguish itself from the sibling match_manufacturers, 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?

There is no explicit when-to-use or when-not-to-use guidance, and no mention of the sibling match_manufacturers as an alternative for a different matching task. Usage is only implied by the phrase 'in the directory'.

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?

readOnlyHint=true already tells the agent this is a safe read. The description usefully discloses the shape of the returned content (summary, explanation, checklist, related tools), which goes beyond the annotation, but says nothing about error behavior for out-of-range steps or whether the payload is large.

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

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

One sentence, front-loaded with the verb and resource, with the payload description compactly parenthesized. No filler or 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 output schema, the description partially compensates by naming the four content sections a step returns. For a simple single-parameter getter this is nearly complete; only error/range-handling behavior is left 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 coverage is 100% and the single parameter is fully documented with a 1–13 range, so the schema carries the semantics. The description's 'one of the 13' merely echoes that bound without adding format or indexing detail. 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?

States a specific verb ('Get') and resource ('playbook step'), plus scope ('one of the 13'). The parenthetical enumerates what a step contains, so the agent knows exactly what it retrieves. No sibling tool overlaps, so no differentiation is needed.

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 guidance on when to use this tool versus anything else, nor any prerequisites or ordering advice (e.g., whether steps must be read in sequence). Usage is only implied by the name and the word 'Get'.

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 readOnlyHint=true already declaring the safety profile, the description adds genuine context beyond annotations: the authentication requirement (a token issued by create_rfq) and the fact that results are partial/in-progress ('received so far'). It stops short of describing pagination or result volume.

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 short sentences with zero waste. The purpose is front-loaded, and the prerequisite requirement follows immediately after.

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 read-only tool with annotations covering safety and no output schema, the description covers purpose, scope, and auth prerequisites adequately. Only minor gaps remain (no mention of result format or growth of matches/quotes over time).

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 schema offers only bare types for rfq_id and token. The description partially compensates by explaining that token is the one returned by create_rfq and that rfq_id identifies the RFQ, but it gives no format or value constraints for either.

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 ('Read') and resource ('the matches and the quotes received so far for an RFQ'), plus the scope that it applies to an RFQ the caller created. This is clearly distinguishable from the write-side siblings create_rfq, submit_quote, and submit_quote_request.

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 prerequisite is stated ('Needs the rfq_id and the token returned by create_rfq'), which implicitly positions this as the follow-up to create_rfq. However, there is no explicit when-to-use vs alternatives guidance and no exclusions, so usage is only implied rather than directed.

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

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

The annotation already declares readOnlyHint=true, so safety is covered. The description adds that returned entries include pros and cons, which is useful return-content context given there is no output schema, but it says nothing about pagination, filtering behavior, or result size.

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 short sentences, front-loaded with the action and resource, with the optional filter last. Nothing is wasted, though the inline category list is slightly dense and has no separator cue distinguishing it from prose.

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, single-optional-parameter listing tool with no output schema, the description covers purpose, allowed filter values, and rough return content. Only minor gaps remain (no pagination or ordering behavior), which is acceptable 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 100% for the single parameter, so the baseline is 3. The description exceeds it by enumerating the accepted category values (Fabrication, Electronics, Sourcing, Prototyping, Measuring, Design, Review), which the schema does not provide since there are no enums declared. This materially constrains how the agent should call the tool.

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 ('List tools and factories') and adds scope by naming what the entries contain ('pros and cons'). It does not explicitly distinguish itself from nearby siblings like find_suppliers or match_manufacturers, so an agent must infer that this is a reference/catalog listing rather than a search.

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 'Optional category' implies when the filter applies, but there is no explicit when-to-use guidance, no prerequisites, and no named alternative among the ten sibling tools. Usage is only weakly 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?

Annotations only declare readOnlyHint=true, so the safety profile is covered; the description usefully adds that results come back scored and accompanied by reasons. That explainability detail matters because no output schema exists, though ranking criteria, tie-breaking, or result limits are still undisclosed.

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, zero filler, and the core action is front-loaded before the return-value detail. Nothing could be cut without losing 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 ranking tool with no output schema and only partial schema coverage, the description covers purpose and return shape but omits how parameters influence ranking, whether results are limited or paginated, and how ties are resolved. Adequate minimum, with clear 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 description coverage is only 44% across 9 parameters, so the description would need to compensate, and it does not: process, materials, industries, certifications, limit, and tolerance behavior are never mentioned. 'Structured part spec' is too vague to map onto any specific 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?

States a specific verb and resource ('Rank manufacturers') plus the input it consumes ('a structured part spec'), which is more precise than a tautology. It does not, however, name or differentiate itself from plausible siblings such as find_suppliers or estimate_product_cost, leaving the agent to 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?

The phrase 'for a structured part spec' hints at the intended input, but there is no explicit when-to-use guidance, no when-not-to-use condition, and no mention of the sibling tools that overlap with this one (find_suppliers, list_manufacturing_tools). The agent must guess at 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?

readOnlyHint=true already tells the agent this is a safe read operation, so the bar is lower, but the description adds nothing beyond that: no ranking behaviour, no result-shape or pagination context, no note on how matches are scored.

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

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

A single front-loaded sentence that names the action and the content set with no filler. It could carry one more useful clause (e.g. limit behaviour) without becoming bloated.

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, read-only search with no output schema and full schema coverage, the description covers what an agent needs to invoke it correctly. Only minor gaps remain around result ordering and limits.

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

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

Schema description coverage is 100% for both parameters (query as free-text term, limit 1-20), so the schema does the heavy lifting. The description adds no extra meaning about query syntax or matching behaviour; 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 (Search) and a precise scope: the playbook, guides, tool reviews and comparisons on a named domain. That is clearly distinguishable from the RFQ/supplier-oriented siblings, though it does not explicitly name a sibling it is not.

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 content scope implies when to use it (looking for documentation, reviews or comparisons rather than suppliers or quotes), but there is no explicit when-to-use, when-not-to-use, or pointer to alternatives such as list_manufacturing_tools.

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 this is a non-read-only, idempotent, non-destructive write, so the safety profile is covered. The description adds a genuine behavioral requirement (the supplier token issued at registration), but says nothing about what submission replaces, whether the quote can be edited afterward, or what happens on a duplicate submit.

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, no filler, with the audience and the core action front-loaded before the prerequisite. Nothing is wasted, though the terseness is part of why other dimensions lose 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 an 8-parameter write tool with no output schema and poor schema description coverage, this is under-specified: it omits the meaning of most parameters, the response behavior, and how it differs from 'submit_quote_request'. An agent could pick this tool but would be guessing at half the payload.

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% – just 'currency' and 'valid_until' carry descriptions – so six parameters (rfq_id, unit_price, quantity, notes, lead_time_days, supplier_token) rely on the description, which only explains the provenance of supplier_token. No units, formatting, or range guidance is added for price, quantity, or lead time.

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 ('answer an RFQ') and the actor ('for a manufacturer's agent'), which lets an agent recognize this as the supplier-side response step. It does not distinguish itself from the sibling 'submit_quote_request', which is a real ambiguity given the near-identical names.

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 ('an RFQ the company was matched to'), implicitly routing the agent through the match flow first, plus the prerequisite token. It names no alternatives or exclusions, but the context 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?

Annotations cover the write/idempotency profile, and the description adds meaningful non-schema behavior: the request is shared externally with manufacturers, a human reviews it, and the reply arrives by email (asynchronous, non-instant). This consent and human-review disclosure is genuinely additive. It stops short of stating what happens on failure or whether the submission can be retracted.

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

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

Three tight sentences, front-loaded with the action, then the gating condition, then the outcome. No filler or repetition.

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 six parameters and no output schema, an agent still lacks detail on the three undocumented optional fields and on what a successful submission returns (an ID? a confirmation?). The description does explain the downstream human-review/email-reply flow, which is the most important missing piece, but not enough 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 only 50%, leaving country, process, and quantity undocumented in both schema and description. The description adds no parameter meaning at all — no note that country/process/quantity are optional, no format guidance for quantity or process selection — so it fails to compensate for the coverage 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?

States a specific verb+resource ("Send a quote request") and clarifies it is on behalf of the human the agent acts for. It does not differentiate itself from close siblings like submit_quote or create_rfq, which an agent could easily confuse with this one.

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?

"Only call after the user agreed that the request and email may be shared" gives a clear, explicit precondition for invocation, and the sentence implicitly warns against premature calls. However, it names no alternative tool or scenario where a sibling (e.g., submit_quote, create_rfq) would be preferred.

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