Rasczak Knowledge Commons

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

With no annotations at all, the description carries the behavioral burden. It is a read-only listing operation ('List...'), which is transparently disclosed. However, it doesn't mention response shape, pagination, or any potential latency or failures; the 'free' qualifier adds a reasonable constraint but is not behaviorally rich.

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 every word earns its place. No restatement 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?

For a zero-parameter catalog/listing tool with no output schema, the description is nearly complete: it tells the agent the kind of information returned. It does not define what fields or pricing structure appear, but the sibling names and tool purpose compensate. A small deduction for not clarifying whether the list is interactive or static.

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 are 0 parameters, so the description's job is trivial; saying what the tool lists (free methods, decision packs, prices) is sufficient contextual meaning. The baseline for 0 params is 4, and the description meets it by clarifying the output category.

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 clear verb ('List') and a resource ('available free methods, decision packs, and prices'), which distinguishes catalog from the sibling tools method, pack_offer, and sample_pack. It doesn't name the siblings explicitly, but the resource enumeration conveys 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 description implies catalog is the tool for browsing available offerings, which is useful context. However, it does not explicitly state when to use this tool versus method, pack_offer, or sample_pack, nor any exclusions or prerequisite 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 the behavioral burden. It discloses that these kits are non-purchasable previews and warns against private-scenario queries, which are meaningful constraints. It does not cover return format, pagination, rate limits, or whether any side effects exist, 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?

Three short sentences, front-loaded with the core action, then adding context and a usage rule. Every sentence contributes value; there is no redundant phrasing 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?

Given no annotations, no output schema, and 0% schema description coverage, the description gives enough to understand the tool's purpose and a key query constraint, but leaves parameter semantics, result shape, and pagination unspecified. It is a minimally adequate description for a simple search tool, 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 description coverage is 0%, and the description only vaguely maps to the q parameter via 'Query using general task words'. It provides no explanations for limit, domain, or offset, and does not clarify parameter formats or expected values beyond schema constraints.

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 'Find work-kit previews', a specific verb and resource that clearly identifies the tool's function. The phrase 'awaiting evaluation and cannot be purchased' adds distinguishing context, though it does not explicitly name or contrast sibling 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?

Provides clear usage context: the kits are awaiting evaluation and cannot be purchased, so the tool is for preview/exploration. It also gives an explicit query rule—'use general task words, never private scenarios'—which functions as a when-not instruction. However, it does not mention alternative sibling tools or conditions for choosing them over this one.

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 disclosure burden. It conveys a read-only operation and promises provenance/limitations in the response, but does not mention errors, access requirements, or behavior for invalid IDs.

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 with no extraneous words. The action, key constraint, and return content are all 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 low-complexity single-parameter read tool, the description covers what to pass and what to expect back. It does not detail the shape of provenance/limitations, but no output schema exists and the tool is simple enough that this is a minor 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?

Although the schema's id property only provides type and maxLength, the description adds semantic meaning: the id must be a 'catalog ID' and must match 'exact[ly]'. This compensates for the 0% schema description 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?

Description states a clear verb ('Read'), a specific resource ('free method'), and a precise filter ('exact catalog ID'). It further specifies the return content ('provenance and limitations'), which distinguishes it from siblings like catalog and pack_offer.

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 'exact catalog ID' implies the intended use case: the caller already has the ID and needs an exact lookup. However, it never explicitly states when to use this tool over siblings, nor gives exclusions or 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 the full burden. It makes a valuable disclosure: this tool has no financial side effects, preempting a dangerous mis-assumption for a payment-related tool. However, it omits other behavioral traits like error behavior on unknown pack IDs, URL expiry, or authentication 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?

Two sentences, roughly 14 words, with the core function front-loaded and the critical safety clarification in the second sentence. Every word earns its place; nothing is redundant 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?

For a low-complexity tool (one simple param, no output schema), the description is reasonably complete: it states the output in prose ('payable HTTP URL and price') and the key exclusion. Gaps remain — what the agent should do with the URL, error behavior, and whether the price is currency-specified — but these are modest for a simple lookup 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 compensate. 'By pack ID' correctly maps the lone `id` parameter to a pack identifier, adding meaning the raw schema lacks. But it adds no further detail about the ID format, where to find it, or validity beyond the schema's maxLength constraint — adequate but minimal compensation.

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 ('Get'), a concrete resource ('a payable HTTP URL and price'), and a lookup key ('by pack ID'). It clearly differentiates this from catalog browsing or sampling tools. The phrase 'payable HTTP URL' is slightly ambiguous about what makes the URL payable, keeping it from 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 explicit negative 'Does not pay, buy, or authorize spending' gives a clear boundary for when NOT to use this tool — it only fetches offer info, payment happens elsewhere. However, no sibling tool is named as the alternative, and the positive usage context is only implied 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 disclosure burden and does meaningful work: it states retention ('Raw feedback retained 30 days'), confirms this is not a commercial transaction ('No order or payment'), and imposes privacy expectations. It could add what happens after submission, but the disclosed traits are substantive.

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 four short, front-loaded sentences with no filler. Every sentence contributes: purpose, privacy requirements, exclusion of order/payment, and retention.

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 privacy and retention context is well covered, but for a tool with 8 parameters, 5 required, and no annotations or output schema, the description is only minimally complete. It does not explain the required identifiers or budget/model fields, although the enum values reduce some 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 0%, so the description must compensate; it only hints at the 'kind' parameter via 'research interest or skill feedback' and leaves client_id, model, budget, rating, comment, human_confirmed, and domain semantically unexplained. The enums are self-explanatory, but the description itself adds little parameter-level meaning.

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-resource pair: 'Submit optional research interest or skill feedback,' and the two feedback kinds map to the schema's kind enum. It does not explicitly differentiate from sibling tools such as research_preview, 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 gives clear how-to-use guidance (use a pseudonym, omit private data) and states this is not for order or payment, but it never says when to choose this tool over alternatives. No sibling is named and there is no explicit when-to-use / when-not-to-use framing beyond the implied feedback 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 provided, the description carries the behavioral disclosure burden. It clearly states the action is a read ('Read') and explicitly disclaims side effects ('No executable quote, payment or job is created'). This is strong transparency for a no-parameter tool, though it could add details about response format or data sources.

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 no filler. The core action and resource are front-loaded, and the disclaimer about not creating anything follows naturally. Every sentence 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 parameterless read-only preview tool, the description is largely complete. It names what is read (scopes and cost policy) and what will not happen. It does not describe the exact output shape, but there is no output schema and the read scope is reasonably clear given the tool 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?

The tool has zero parameters, so there is no parameter documentation burden. The description does not need to explain parameters, and the baseline of 4 applies because the description correctly orients the agent without schema-driven 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 uses a specific verb ('Read') and names a clear resource ('future hosted research scopes and cost policy'). It also explicitly states what the tool does NOT do ('No executable quote, payment or job is created'), which helps distinguish it from tools that actually create or execute work.

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 this is a preview/read-only tool and that no commitments are made, which is a usage signal. However, it does not explicitly mention when to choose this over sibling tools or state any exclusions or prerequisites. The guidance is present but mostly implicit.

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 burden of behavioral disclosure. It does disclose a meaningful behavioral trait: the operation requires neither payment nor an account. However, it does not state whether the tool is read-only, what the output will look like, or whether any action or download is triggered.

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 one short sentence plus one clarifying sentence. Both sentences earn their place: the first states the offer, the second removes common friction concerns. There is no redundancy or 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?

Given the zero-parameter schema, the description is minimally viable: it tells the agent that an evaluation pack is available for free without an account. Still, it lacks any orientation toward what the agent should do with the tool, what the pack contains, or how the sibling tools relate, so completeness is only moderate.

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?

This tool has zero parameters, so the schema is trivially complete and there is no parameter semantics burden for the description. The baseline for zero-parameter tools is 4, and the description does not need to explain missing 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?

The description identifies the resource as a 'complete vendor-evaluation pack' and indicates it is free, but it lacks an explicit action verb (e.g., 'retrieves', 'downloads', 'delivers'). It does not distinguish this tool from its siblings catalog, method, or pack_offer, so an agent cannot confidently know what makes sample_pack unique.

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 no payment or account is required, which could be a prerequisite and a token of trustworthiness. However, there is no explicit statement about when to choose this tool over the sibling tools, nor any exclusion or alternative cue. The agent is left to infer usage from the name.

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