Sigistry Plugin Catalog (formerly Claude Registry)

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

Annotations already declare the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds value beyond annotations by disclosing what the response includes (install commands, component counts, and the per-check pass/fail security result), which is genuinely useful behavioral context. No contradiction with 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?

A single, front-loaded sentence that leads with the tool's core purpose and packs the return-value details without padding. Every clause earns its place; there is no redundant restatement of the name or title.

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 a simple single-parameter read, the safety profile is fully covered by annotations, and an output schema exists, so return values need no description. The only shortfall is the missing guidance on how get_plugin relates to verify_plugin for security-audit needs, but the definition is otherwise complete for correct invocation.

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

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

Schema description coverage is 100% — the single id parameter is already documented in the schema with an example ('sql-safety-net'). The description only restates that the tool operates 'by its id', adding no new semantics over the schema. Baseline 3 applies because the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get the full details of a single Sigistry plugin by its id') and enumerates the return content (install commands, component counts, security-audit result). This clearly differentiates it from siblings list_categories and search_plugins, which operate at a different scope and grain.

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 context — you call this when you already have a plugin id and want full details — which is clear from 'by its id'. However, it names no alternatives or exclusions, and the security-audit portion overlaps with the sibling verify_plugin without any guidance on which tool covers that need. Meaningful but 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?

Annotations already mark this as read-only and idempotent, and the description adds meaningful behavior: returns the full portable source, is safe for direct use in any SKILL.md-aware agent, and has passed the Sigistry safety check. This goes beyond the schema and annotations without contradicting them.

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 concise, front-loaded with the core action, and each sentence earns its place by explaining the returned content, how to use it, and the verification guarantee. There is no fluff or repetition of schema details.

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

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

For a single-parameter read-only tool with a rich output schema, the description covers what the tool returns, how portable the result is, how to discover valid names, and what verification status means. An agent has enough to decide when and how to call this correctly without further digging.

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 'name' already includes an example and guidance to use search_skills for discovery. The description adds little parameter semantics beyond 'by name' and does not need to, given the schema already carries the necessary detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the specific verb ('Get'), the resource ('one Sigistry skill'), and the key content ('full raw SKILL.md source'), making the purpose immediately clear. It also differentiates from sibling tools like search_skills and get_plugin by emphasizing portability and verification.

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

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

The description clearly explains how the result can be used (applied directly or installed natively) and references search_skills for finding skill names. It does not explicitly state when to prefer siblings like get_plugin over get_skill, but the context strongly implies the distinction.

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 and idempotent, so the description does not need to restate safety. It adds behavioral detail by specifying the return structure (count per category and total plugin count), which goes beyond annotations. No contradictions.

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

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

Single sentence, front-loaded with the verb 'List', includes key output details without redundant language.

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 read-only tool with an output schema, the description adequately explains what the tool returns. It names the marketplace context (Sigistry) and the specific aggregate counts.

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?

No parameters exist, so baseline 4 applies. The description compensates with a clear output definition, making it unnecessary to document any 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?

States a specific verb (list), a resource (plugin categories), and distinguishes itself from siblings (get_plugin, search_plugins) by describing an aggregate count operation. It clearly defines the scope: distinct categories with per-category counts plus total.

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?

Does not explicitly state when to use this tool or alternatives. The purpose implies usage when one needs an overview of categories, but the description lacks explicit when/when-not guidance. Sibling tools exist, so some guidance would help.

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 provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context by disclosing that results include install commands and verification status, and that the registry runs an eight-check security audit. This enriches the agent's decision-making 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?

Two sentences front-load the action and scope, then concisely add return details and practical selection guidance. There is no filler, repetition of schema fields, or irrelevant 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 simple, read-only search with two optional parameters, an output schema, and strong annotations, the description covers the search target, the matching dimensions, result contents, and the security signal to prioritize. Nothing critical is missing for correct selection and invocation.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds value by clarifying the relationship between the two parameters with 'by keyword and/or category', indicating query and category can be used independently or together—something the individual property descriptions do not explicitly state.

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, resource, and marketplace: 'Search the Sigistry marketplace of Claude Code plugins by keyword and/or category.' It also states what is returned (install command, verification status), which clearly distinguishes plugin search from sibling tools like get_plugin or search_skills.

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

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

The description gives clear context for when to use the tool: when searching marketplace plugins by keyword or category. It does not explicitly name alternatives or exclusion conditions, but the search scope and the added recommendation guidance ('prefer verified plugins') make the intended usage obvious.

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 read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by explaining the 'verified' status and the safety-check criteria, giving agents confidence in result quality. It does not mention pagination or ordering, but the output schema covers return structure.

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 concise sentences, each earning its place: the purpose sentence defines the resource and filter, the second explains trustworthiness, and the third routes to the correct next sibling. Information is front-loaded and there is no filler.

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

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

For a low-complexity search tool with a rich output schema and safety annotations, the description covers purpose, scope, safety, and next steps. It leaves minor gaps such as behavior with no query and explicit differentiation from search_plugins, but the core invocation needs are met.

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 query and plugin are already well documented. The description restates 'by keyword' and 'parent plugin' in prose but adds no new parameter-level meaning beyond what the schema already provides.

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 specific verb ('Search'), a precise resource ('Sigistry catalog of verified skills'), and the optional plugin filter. It also clarifies that skills are SKILL.md instruction sets, distinguishing it clearly from sibling tools like search_plugins and get_skill.

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

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

The description clearly positions search as the discovery entry point and explicitly directs the agent to use get_skill for fetching the source of a match. It does not explicitly contrast with search_plugins or list_categories, so it stops short of full when-to-use guidance for all siblings.

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 description goes well beyond the readOnly/idempotent/destructive annotations by disclosing that verification runs entirely locally, the plugin code never leaves the user's machine, and the server performs no computation. It also clarifies that the tool returns a recipe to follow rather than performing the verification itself, which is a crucial behavioral caveat.

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 detailed but efficient: it states the purpose, enumerates the checks, explains the privacy model, and gives usage instructions without redundancy. The important behavioral facts are front-loaded before the longer list of checks.

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 one optional parameter and an output schema, the description is complete. It tells the agent what the tool does, when to call it, what steps to follow afterward, and what privacy/execution behavior to expect. The existence of an output schema covers return-value details.

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

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

Schema coverage is 100%, so the schema already documents pluginPath as an optional local path used to fill in the run command. The description reinforces this by referring to running the script against the plugin directory, but it adds little meaning 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 leads with a specific action ('Get the recipe to run the Sigistry verification methodology') tied to a clear resource (verifying a Claude Code plugin before publishing). It distinguishes itself from sibling lookup/search tools by focusing on the pre-publish verification workflow rather than fetching or searching plugin data.

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

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

It explicitly tells the agent when to call it: 'Call this when the user wants their plugin or skill checked.' It also gives follow-up steps the agent should relay. It does not explicitly state when not to use it or compare against sibling alternatives, but the usage context is clear.

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