MCP CPG Agent Protocols

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

No annotations are provided, so the description bears full responsibility. It discloses the version (v3.2), lock date, and that the output is the canonical list. It does not state side effects or idempotency, but the nature (get) suggests read-only, and the detail is high for a simple retrieval.

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: one defines the resource, the second adds actionable context. Every word is necessary; 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?

Given no parameters and no output schema, the description sufficiently explains what is returned (canonical list of 18 headers) and provides version context. It is complete for a simple retrieval tool, though it could mention typical use cases.

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 no parameter information is needed. Baseline is 4 per guidelines, and the description does not need to add param info.

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 the GSC wire-header canon, specifically the eighteen x-gsc-* headers in canon order. It uses specific verbs and resources, and distinguishes itself from sibling tools (e.g., list_protocols, list_members) by focusing on headers.

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

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

The description implies usage for auditing against live GSC surfaces ('Curl-auditable against any live GSC surface'), but does not explicitly state when to use or exclude alternatives. Usage is 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 behavioral burden. It discloses that the result is a 'Full canon record', but does not address side effects, authentication needs, error behavior, or response shape. For a fetch operation this is minimal but not misleading.

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 with no filler. It states the purpose, the scope, and the exact accepted values, making it easy to scan and parse.

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 required enum parameter and no output schema. The description says what is returned ('Full canon record') but not what that record contains or when to reach for this tool over siblings. This is adequate but leaves some context to inference.

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 'name' parameter is fully defined by its enum and description. The description adds no new semantic detail about the parameter beyond restating the allowed values, so the baseline of 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 ('Full canon record') and enumerates the exact protocol identifiers it applies to: ACM-SPARKS, SM-ECO-10060, and ACM-68000. It clearly differentiates from list_protocols and other sibling getters by indicating a single, full-record retrieval.

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: use this when you need the full canon record for one of the three named protocols. However, the description does not explicitly state when to prefer list_protocols or mention any exclusions, leaving the agent to infer the distinction from the title and sibling names.

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 only describes what is listed (static metadata) but does not disclose behavioral traits such as side effects, rate limits, or authentication requirements. Listing is assumed read-only but not confirmed.

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-loading the core purpose and adding a clarifying scope note. 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?

Given no output schema, no parameters, and low complexity, the description is almost complete. It explains what is listed and the fields included. Minor gap: no mention of authentication or pagination, but acceptable for a simple list 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?

The input schema has no parameters (100% coverage). The description adds meaning by enumerating the output fields (code, namespace, jurisdiction, region, GS1 territory GTIN), which the schema did not provide. This is a helpful clarification.

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 it lists '49 sovereign jurisdictional member nodes' with specific fields (code, namespace, jurisdiction, region, GS1 territory GTIN). This verb-resource combination is specific and differentiates from sibling tools like get_header_canon or list_protocols.

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 tool is for metadata only by stating 'Live supply/demand data per member is the CPG Knowledge Graph's job,' but it does not explicitly provide when-to-use or when-not-to-use guidance nor name alternatives for live 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?

No annotations are provided, so the description must convey behavior. It fails to state that the tool is a read operation, does not describe side effects, permissions, or return characteristics. The cryptic text adds no behavioral insight.

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 short but at the expense of clarity. It is cryptic and uses jargon without explanation, making it unhelpful. Conciseness requires effectiveness, not just brevity.

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 no output schema, yet the description does not describe what is returned. For a listing tool, the agent needs to know the output format or content. The description is entirely inadequate for an agent to understand the tool's behavior.

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 is empty with 100% coverage, meaning no parameters. The description does not add meaning beyond the schema, but absent parameters, a score of 3 is baseline. The description does not explicitly confirm that no input 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 title states 'List the three GSC protocols', providing a clear verb and resource, but the description is cryptic and does not reinforce or clarify the purpose. It mentions protocol family and specific codes without explaining that the tool lists them.

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

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

There is no guidance on when to use this tool versus alternatives. Siblings like 'get_protocol' exist but no comparison or context is given. The description does not help an agent decide when to invoke this tool.

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

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

No annotations are provided, so the description bears full responsibility. It adds 'One meaning, no drift' indicating stability of signals, but does not disclose whether the operation is read-only, requires permissions, or has other behavioral traits. For a simple list operation, the description provides some context but lacks completeness.

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 extremely concise with two sentences, front-loading the enumeration of signals. No redundant information; 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 the tool's simplicity (no parameters, no output schema), the description is nearly complete. It lists all seven signals and adds stability context. However, it could explicitly state that the output is a list of signal identifiers, though the name and context imply 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?

The tool has zero parameters, and schema coverage is 100%. The description adds no parameter-specific information, which is acceptable as baseline is 4 for zero parameters. No additional value is needed 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?

The description explicitly states that the tool lists all seven signals of the ACM-68000 set, naming each individually. It clearly distinguishes from the sibling tool 'resolve_signal', which likely retrieves a single signal, by focusing on enumeration of the complete set.

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

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

The description implies usage for obtaining all signals, but does not explicitly state when to use this tool over alternatives like 'resolve_signal'. No exclusions or prerequisites are mentioned, leaving the agent with implied but not explicit 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?

No annotations are provided, so the description must convey behavior. It indicates a read-only query returning a predefined set of six dimensions, which is sufficient for a simple list tool. No side effects are implied, but the use of 'resolves' is slightly ambiguous.

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 clear sentence, front-loaded with the core purpose. Every word adds value; no wasted text.

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 zero parameters, no output schema, and low complexity, the description covers the essential: it lists the dimensions. It could mention the return format or data type, but it is sufficiently complete given the tool's simplicity.

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 zero parameters, so schema coverage is 100%. The description adds no parameter info, but none is needed. Baseline 4 is appropriate since parameters are absent.

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 tool lists the six SPARKS dimensions, using a specific verb (list) and resource (dimensions), and names each dimension. This clearly distinguishes it from sibling tools like resolve_sparks_dimension.

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 the tool is used to retrieve the list of dimensions, but does not explicitly state when to use it vs. resolve_sparks_dimension or other siblings. No exclusions or prerequisites are mentioned.

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 burden of behavioral disclosure. It only says the result is a 'canon record' for a single member; it does not state whether the operation is read-only, what it returns, how unknown or invalid codes behave, or any freshness/authority semantics behind 'canon'.

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-loads the resource, scope, and keying mechanism, and the examples earn their place. There is 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?

For a one-parameter lookup tool the essential invocation data is present, but with no annotations and no output schema, the description should at least hint at return shape or error behavior to be fully complete. It also leaves the term 'canon' undefined, which may confuse an 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?

The schema already documents the single code parameter at 100% coverage, but the description adds real value by specifying 'ISO-style' and giving examples (FR, AU, MX), which clarifies the expected format and namespace beyond the schema's generic 'Member code, e.g. FR'.

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 a single sovereign member as the resource, keyed by ISO-style code, with concrete examples (FR, AU, MX). It is distinguishable from list_members and the other resolve_* siblings by the explicit 'single' and member scope, though it relies on the title's 'Resolve' verb rather than stating an explicit verb like 'gets' or 'returns'.

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 reader to use this when they need the canonical record for exactly one sovereign member by code, which is clear context. However, it never explicitly contrasts it with siblings such as list_members for bulk lookup or resolve_signal for signals, so no exclusionary guidance is provided.

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 it clearly states the core behavior: a CPG- profile code resolves to its ACM- twin and the response contains the resolved ACM- code. It does not cover unknown-code or error behavior, but for a simple read-style resolver the main contract is 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 short and front-loads the object being resolved, with no filler. The first sentence is a noun phrase rather than a complete sentence, which slightly hurts readability, but the second sentence carries the key behavioral detail efficiently.

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 one parameter, no output schema, and no annotations, the description covers the essential input/output contract: single signal code in, resolved ACM- code out. It could specify the exact shape of the state/meaning payload or behavior when an ACM- code is passed directly, but these are minor for a simple resolver.

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 fully documents the code parameter with examples, so the baseline is 3. The description adds semantic value by explaining that CPG- profile codes map to their ACM- twins, which clarifies the expected input and the direction of resolution.

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 title and description identify a specific operation—resolving one signal code—and the resource is a single ACM-68000 signal. It goes beyond a tautology by specifying the CPG- to ACM- mapping, which distinguishes it from sibling list tools like list_signals.

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 CPG- to ACM- twin mapping implicitly tells an agent when to use this tool: given a profile code, obtain its canonical ACM- equivalent. However, it never names alternatives or states exclusions, leaving the selection logic 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 burden of disclosing behavior. It only says the result is a 'Canon record' without explaining what that record contains, whether the lookup is read-only, how invalid inputs are handled, or whether lookup is case-sensitive.

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 sentence with no filler. It front-loads the tool's purpose ('Canon record for a single SPARKS dimension') and immediately gives the accepted input forms.

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 lookup tool with 100% schema coverage, this is minimally adequate for invocation. However, with no output schema and no annotations, the description should disclose more about the returned canonical record, error behavior, or accepted name variants, and 'Canon record' is left underspecified.

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 description largely repeats what the schema already states: the dimension can be a letter or name. It adds the explicit S2 letter, but does not meaningfully enrich parameter semantics 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?

The description clearly identifies the resource type (a single SPARKS dimension) and the lookup key (letter or name). It also distinguishes itself from list_sparks_dimensions by emphasizing 'single'. However, it uses the noun phrase 'Canon record for' instead of an explicit verb like 'resolve' or 'returns'.

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 explicit: the description says it handles a single dimension by letter or name, which suggests using it when one specific dimension is needed. It does not state when to prefer list_sparks_dimensions or other sibling tools, and it gives no exclusion criteria.

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