Fractera

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

Annotations declare readOnlyHint=true and destructiveHint=false. The description goes further by detailing behavioral traits: it is a one-time read on demand, the deployment timing (8-14 minutes), and the return content (current step, completed steps, done/failed). This adds valuable context without contradicting 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?

The description is four sentences, front-loaded with purpose and usage. Every sentence provides essential information without redundancy, earning its place. It is both concise and well-structured.

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 has one parameter, no output schema, and no nested objects, the description is complete. It explains what the tool returns (current step, completed steps, done/failed), which is critical since there is no output schema. No gaps or ambiguities remain.

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 one parameter (session_id) with a description, and coverage is 100%. The description does not add new details about the parameter itself, but it provides context by stating where the session_id comes from (register_and_deploy or retry_deploy). This is marginally helpful, meeting the baseline for high schema 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?

The description clearly states the tool reads current installation progress on demand, specifies the verb ('Read'), the resource ('current installation progress'), and distinguishes from sibling tools like register_and_deploy and retry_deploy. It explains when to call (user explicitly asks, never on timer or polling), making its purpose unambiguous.

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 provides explicit usage guidance: call only when the user explicitly asks about deployment status, never on a timer or in a polling loop. It also mentions authoritative status channels (email pipeline + dashboard), helping the agent decide when to use this tool versus alternatives.

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 indicate readOnlyHint=true and destructiveHint=false. The description adds value by detailing what is returned (diagram URL, overview, section list) and the branching behavior of the loop. 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?

The description is verbose, explaining the entire loop in detail. While it is well-structured and front-loads the main purpose, it could be tighter. It earns its place but is longer than necessary.

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 no output schema and one optional parameter, the description is thorough: it covers the main output (diagram URL, overview, section list), the two invocation modes, and provides an executive summary of the loop. No gaps remain.

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% with a clear description for the 'section' parameter. The description further explains the two usage patterns and gives example section IDs (e.g., 'hermes', 'lightrag'), adding semantic value 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 states the tool explains the Fractera development loop, returning a diagram URL and overview. It distinguishes itself from sibling tools, which handle other aspects like project info, deployment, or subdomain details.

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

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

Explicitly says to use when user asks 'how Fractera builds software' or 'how its agents work'. Provides two call patterns: no arguments for diagram+overview, or a section id for in-depth reading. Does not mention alternatives or when not to use, but context is clear.

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 and destructiveHint=false. The description adds detailed behavioral context: it returns a diagram image URL, overview scenario, section list, or in-depth entity details depending on arguments. This goes 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?

The description is relatively long but packs significant information. It front-loads the purpose but could be slightly more concise. Every sentence adds value, but the length is acceptable for the complexity of the tool.

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 no output schema, the description covers the key behaviors: both invocation modes, what is returned, and a link to the diagram. It lacks mention of edge cases or limitations, but overall is 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?

Schema coverage is 100% with one parameter described. The description adds value by providing example section ids (e.g., 'hermes', 'lightrag') and explaining the behavioral difference between omitting and including the parameter, which enriches the schema's description.

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 returns an architecture reference for Fractera AI Workspace, including a diagram image URL. It uses a specific verb 'get' and resource 'AI workspace architecture', distinguishing it from siblings like check_status or get_ai_development_loop_info.

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 explicitly says to call when the user asks what Fractera is or how it works, and explains two invocation modes (no arguments vs. with a section id). While it doesn't explicitly list exclusions or alternatives, the provided context is clear and sufficient.

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 and destructiveHint=false, so the tool is safe. The description adds critical behavioral details: the token economy (call with no args for lightweight list, then with section id for full content), and the lang parameter for Russian users. No contradictions 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?

The description is well-structured, starting with the purpose, then specific instructions, and a note on language. It is informative but slightly verbose; every sentence is useful, though some redundancy could be trimmed. Still, it remains clear and scannable.

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 absence of an output schema, the description fully explains what the tool returns: a lightweight list of section ids and titles when called with no arguments, or the full content of a specific section when called with a section id. It covers both invocation patterns and the lang parameter, making it complete for an agent to use correctly.

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

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

Schema coverage is 100% with both parameters described. The description adds meaning beyond the schema: it explains the exact usage pattern (omit section for table of contents, provide section id for content) and clarifies when to use the lang parameter. While the schema descriptions are adequate, the description enriches the context.

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 is a 'Project reference / help desk about Fractera' for answering any user question about Fractera. It distinguishes from siblings by specifying broad coverage (architecture, components, modes, etc.) while siblings like check_status or get_subdomain are more narrowly focused.

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

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

Explicitly says 'use this to answer ANY user question about Fractera' and gives a when-not context: 'especially while a deploy is running and the user wants to learn more'. It provides a clear two-step process (token economy) with specific instructions on how to call the tool effectively.

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 it as read-only and non-destructive. The description adds context about the phase-1 address format (HTTP, IP, no domain/HTTPS), which goes beyond 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?

Description is well-structured with purpose, format, and usage instructions in a few sentences. Slightly verbose but each sentence 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 simple single parameter and no output schema, the description fully covers what the tool returns and when to use it, including edge cases like phase-1 constraints.

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%; the description does not add meaning beyond the schema's description of the session_id parameter. Baseline score 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 clearly states that the tool returns the final entry address of the server after installation, specifying the form in phase-1 and distinguishing it from siblings like check_status and get_project_info.

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

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

Explicitly says to call this after check_status reports 'done', providing clear usage context. Does not explicitly mention when not to use, but the instruction is sufficient.

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 and destructiveHint=false, so the agent knows the call is safe. The description adds workflow context (user buys and returns) that goes beyond the annotation's safety signal.

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. First sentence conveys purpose and condition, second sentence provides actionable next step. Front‑loaded and efficient.

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?

Adequate for a simple zero‑parameter tool, but lacks explicit description of the output format (e.g., expected fields like provider name, plan). With no output schema, the description should clarify what 'recommended VPS provider' means structurally.

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% with no parameters, so the baseline is 3. Description adds no parameter details, but none are 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?

Clearly states the tool returns a single recommended VPS provider for users without a server. Unambiguous verb and resource, and distinguishes from sibling info tools by its specific subject.

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

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

Explicitly states when to call: only when user explicitly says they have no server. Implies when not to use (if user has a server) and provides step‑by‑step expectation of subsequent user 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?

Beyond the destructiveHint annotation, the description discloses exactly what happens: creates/reuses User, creates Subscription and ServerToken, 'wipes any previous installation,' and launches bootstrap. It also explains the IP-first HTTP deployment and notes that domain/HTTPS is deferred, adding material behavioral detail not inferable from annotations or schema.

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 lengthy but information-dense; every sentence adds critical operational detail for a complex, destructive action. It is front-loaded with purpose and flows logically through preconditions, effects, runtime behavior, return values, and usage constraints. Slightly overlong as a single paragraph, but 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?

For a high-complexity deployment tool with no output schema and only two annotations, the description is remarkably complete: it covers preconditions, atomicity, side effects, deployment timeline, network protocol, return values, and interaction with sibling tools. This fully compensates for missing structured output metadata.

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 the schema already documents every parameter in detail. The main description adds context around the overall workflow but does not introduce new parameter-specific semantics beyond what the schema states, so the baseline of 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?

The description opens with a specific verb+resource: 'Register a new Fractera user and start the deployment of their server in one atomic call.' It clearly distinguishes from siblings like retry_deploy and check_status by framing this as the initial deployment action.

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?

Explicit preconditions are stated ('Use this AFTER you have collected the user's email...'), and it specifies call frequency ('AT MOST ONCE per conversation'). It also directs to check_status for a single read and retry_deploy for recovery, giving clear when-to-use and when-not-to-use 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?

Annotations already indicate destructiveHint=true and readOnlyHint=false. The description adds context by stating 'Wipes the previous broken install', which reinforces the destructive behavior and explains what gets destroyed. It also discloses that the tool returns a new session_id, adding behavioral detail beyond 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?

The description is two sentences, front-loaded with the core action. Every phrase earns its place: source of token, destructive effect, fresh deploy, return value, and explicit usage trigger. 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?

Given the tool's complexity (destructive retry, multiple optional parameters), the description covers the key aspects: what it does, when to use it, behavior, and return with polling reference. No output schema exists, but the description compensates by mentioning session_id and check_status. Annotations cover safety, and schema covers all parameters.

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 baseline is 3. The description adds extra meaning by specifying the server_token sources (failure email, UI, dashboard) and clarifying that omitting components reinstalls the full recommended toolset. This goes beyond the schema field descriptions.

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 retries a failed deployment, with a specific verb ('Retry') and resource ('failed deployment'). It distinguishes from sibling tools by noting it wipes the previous broken install and runs a fresh deploy on the SAME server, and mentions returning a new session_id to poll with check_status.

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 explicitly says 'Use this when the user reports a failed deploy or pastes a server_token', providing clear usage context. It also references register_and_deploy for components, implying a distinction, but does not explicitly state when not to use it or name alternatives for exclusion.

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