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

With no annotations provided, the description carries the full burden. It discloses a critical behavioral trait: it validates dependency references and checks for cycles before inserting. This goes beyond the basic 'add' action and informs the agent about potential rejection errors. However, it does not describe what happens if validation fails or how the graph is persisted, leaving some transparency 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?

The description is exactly two sentences: the first front-loads the primary action and context, and the second adds the key validation behavior. Every word is purposeful; there is no fluff, repetition, or extraneous detail. It is 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 13 parameters and no output schema, the description covers the core purpose and validation but leaves important gaps. It does not mention what the tool returns (e.g., the created node or updated graph), what happens if validation fails (beyond 'checks before inserting'), or whether the graph must already exist. These details are relevant for an agent using the tool with complex state and no structured output guidance.

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 54% (7 of 13 parameters have descriptions), so the description must add some value. It notes that phase and category are optional, and it explains that dependency references are validated, which gives meaning to the depends_on parameter. However, it does not add semantic context for many parameters like priority, max_attempts, or output_artifacts, leaving the burden on the schema or the parameter names themselves.

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 action ('Add'), the resource ('new task node'), and the target context ('into the active workflow graph'). It distinguishes itself from siblings like update_task_node and reset_task_node by specifying 'new' and 'dynamically'. The added clauses about dependency validation and cycle checking further clarify the tool's specific role.

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 creating new nodes but does not explicitly mention when to use it over alternatives such as update_task_node or reset_task_node. It provides context ('dynamically', 'active workflow graph') but lacks explicit exclusions or naming of alternative tools for comparison.

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 burden. It discloses the exact behavior: which statuses are reset and that COMPLETED nodes are skipped. However, it does not mention irreversibility, side effects on tasks, error handling for invalid phase names, or whether the operation returns a summary.

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, well-structured sentence that leads with the main action and scope. It includes the key detail about skipping COMPLETED nodes without any superfluous words. Excellent conciseness.

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 only two parameters, no output schema, and no annotations. The description covers the core operation and key edge case (COMPLETED nodes). It could mention return values or whether partial failures are possible, but for its simplicity it is fairly 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 100%, and both parameters already have detailed descriptions in the schema. The tool description adds no significant parameter semantics beyond what the schema already provides, just rephrases includeInProgress as 'optionally IN_PROGRESS'. 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 explicitly states the action ('Reset'), the target (nodes in a phase), the scope (FAILED and optionally IN_PROGRESS), and the resulting state (PENDING). It clearly distinguishes this bulk operation from sibling tools like reset_task_node by specifying 'in a phase' and the status conditions.

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 use case: reset multiple nodes in a phase rather than individually. However, it does not explicitly compare with alternative tools (e.g., reset_task_node for single-node resets) or state when not to use the tool, such as when only a single node needs resetting.

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 must disclose behavior, and it does: 'Retrieve' signals a read-only operation. The list of returned data (ASCII table, Mermaid, phase progress, nodes, errors, timeline) adds transparency about what the tool exposes, though it doesn't mention potential side effects or environmental dependencies.

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, well-structured sentence that front-loads the core purpose and then enumerates the included data. Every word carries meaning, with no redundancy 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?

Despite lacking an output schema, the description enumerates the major sections of the returned state, giving the agent a clear picture of what to expect. The optional boolean parameters are fully documented in the schema, so the tool is completely usable based on this description.

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 provides 100% coverage for both parameters with clear descriptions of the boolean flags (includeMermaid, includeAsciiTable). The description adds no extra parameter detail, 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 uses the specific verb 'Retrieve' with the resource 'current workflow graph state', and enumerates the exact contents (ASCII table, Mermaid diagram, phase progress, nodes, error logs, execution timeline). This clearly distinguishes it from sibling tools like get_phase_status or get_node_timeline, which target narrower aspects.

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 a comprehensive state snapshot but does not explicitly state when to use it over alternatives. It mentions no exclusions or direct comparisons with sibling tools like get_phase_status, leaving the agent to infer the appropriate 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 full burden of behavioral disclosure. It clearly states what is returned (timestamped attempts, exit codes, error logs, duration in milliseconds) and implies a read-only operation via 'Get'. It does not mention permissions or side effects, but for a read-only retrieval tool this is sufficient. It adds value by detailing the contents beyond the tool name.

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, well-structured sentence that front-loads the core purpose and then lists the included data elements. There is zero waste, and every phrase contributes to understanding what the tool does.

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 parameter and no output schema, the description adequately explains the expected output (timeline contents). It does not mention any limitations or edge cases (e.g., behavior if node not found), but the tool is simple enough that this is not a critical gap. The description is complete enough for an agent to select and invoke the tool 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?

The schema has 100% description coverage for the only parameter, nodeId, described as 'ID of the node'. The tool description adds no additional meaning about the parameter beyond what the schema already provides. Since coverage is high, 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 uses a specific verb 'Get' with a clear resource 'chronological execution timeline for a node' and lists the exact contents (attempts, exit codes, error logs, duration). This clearly distinguishes it from sibling tools like get_graph_state or get_phase_status, which target different scopes (graph-level vs node-level).

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: when you need detailed node-level execution history with timing and error logs. It does not explicitly name alternatives or state exclusions, but the specificity of 'for a node' provides clear guidance relative to the sibling tools like get_phase_status. A 4 is appropriate because the context is clear, though no explicit when-not-to-use is given.

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 carry the full burden. It discloses the return contents but does not mention side effects, read-only nature, prerequisites, or error behavior. Since 'Get' weakly implies read-only, it doesn't explicitly confirm safety or provide operational context.

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 concise sentence that front-loads the core purpose and lists key outputs without any fluff. Every word adds value, making it highly 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?

The tool has one optional parameter and no output schema, and the description covers the main return elements (progress summary, percentages, statuses, blocking reasons). It omits detailed output structure but is adequate for a simple getter with low 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?

The schema covers 100% of parameter descriptions ('phase' with 'Specific phase name to inspect (omit for all phases)'), so the description adds no extra parameter semantics. The baseline of 3 applies since 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?

The description clearly states a specific action ('Get') and resource ('phase progress summary'), and enumerates the contents: completion percentages, gate statuses, and blocking reasons. It is well-differentiated from siblings like get_graph_state or get_ready_tasks by focusing on phase-level 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 implies when to use—when phase progress details are needed—but does not explicitly mention alternatives or exclusions. It lacks guidance on how this compares to get_graph_state or get_ready_tasks, though the specificity of 'phase progress' gives some contextual hint.

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 explicitly uses 'Get', indicating a read-only operation, and clearly states the selection criteria. It does not disclose potential edge cases (e.g., empty results) or further behavioral details, but for a simple getter, this is sufficiently 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 a single sentence of 16 words, front-loaded with the action and resource. Every word adds meaning, with no redundant fluff or unnecessary 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?

Given the tool's simplicity (no params, no output schema), the description adequately conveys the purpose and return type (task nodes). It could be slightly more explicit about the return format or fields, but the context is sufficiently complete for an agent to know what to expect.

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 the baseline is 4. The description adds no parameter details, which is appropriate since there are none. It does not mislead or introduce confusion about 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 clearly specifies the action (get) and the resource (task nodes), with a precise condition (dependencies and phase gates satisfied). This distinguishes it from sibling tools like get_graph_state, which retrieves the entire graph, and start_task, which begins 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 usage—use when you want to know which tasks are ready—but it does not explicitly state when not to use it or mention alternative tools. No exclusions or comparisons are provided, so guidance is limited to the implied 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether the tool overwrites existing graphs, creates/persists a state file, how validation commands are executed, or what side effects occur. For a mutation tool with 5 parameters, this is a significant gap.

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 that is front-loaded with the key action and includes a compact list of what the graph contains. There is no redundancy or fluff, making it highly 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's complexity (5 params, nested node objects) and lack of an output schema, the description is insufficient. It does not explain the tool's behavior, what happens after initialization, how state persistence works, or what the agent should expect as a result. This under-specification makes it hard for an agent to invoke safely.

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 100% parameter description coverage, so the schema already documents all parameters. The description's mention of task nodes and validation commands adds minimal value beyond the schema, and no additional semantic detail is provided for parameters like projectRoot or stateFilePath.

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 ('Initialize') and clearly identifies the resource ('project workflow graph') along with key components (task nodes, phase milestones, dependencies, validation commands). This distinguishes it from sibling tools like add_task_node or get_graph_state, which serve different purposes.

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 'Initialize a new' provides clear contextual guidance that this tool is for creating a new graph, not modifying an existing one. However, it does not explicitly mention alternatives or exclusion cases (e.g., when to use add_task_node instead), though the 'new' qualifier provides reasonable clarity.

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 of behavioral disclosure. It mentions Zod schema validation, which is useful, but omits critical behaviors: whether the load replaces the current in-memory state, what happens on validation failure, return value semantics, and side effects. For a mutation-like tool, this is a significant gap.

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, focused sentence that conveys the core purpose and a key validation trait. No wasted words, and the critical information is front-loaded. It earns its place perfectly.

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 description explains what the tool does and its validation approach, but for a load tool with no output schema, it should clarify the effect on the current graph state (e.g., overwrites in-memory state) and error behavior on invalid JSON. Sibling tools provide context, but the description alone is not fully complete for an agent to anticipate side effects.

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 provides full coverage (100%) with a single parameter 'filePath' described as 'Source JSON file path'. The description adds no extra meaning beyond the schema (e.g., file format, required extension, path resolution). Baseline 3 is appropriate since the schema already documents the parameter adequately.

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's function: loading a workflow graph state from a JSON file on disk. The inclusion of 'with full Zod schema validation' distinguishes it from simple file reads, and the contrast with sibling tools like save_graph_state and get_graph_state clarifies its unique role.

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: restoring a graph state from a persisted JSON file. It implicitly distinguishes from get_graph_state (which likely retrieves current in-memory state) and save_graph_state (which persists state). However, it does not explicitly state when not to use this tool or name alternatives, so it falls short of full 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 carries the full burden. It explicitly discloses that the tool resets status and clears error logs, which is a destructive action. However, it does not mention reversibility or side effects on dependent tasks, leaving some behavioral context unexplained.

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, front-loaded sentence that efficiently communicates both the action and its effect with no redundant 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 simple single-parameter reset tool with no output schema, the description adequately covers the action and outcome. It could mention what happens to dependent nodes or whether the reset is irreversible, but overall it is sufficient for this tool's 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% with nodeId described as 'ID of the node to reset'. The description adds context about the reset operation's effect but does not provide additional parameter details, formatting, or examples beyond what the schema already covers.

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 verb (reset), the target resource (task node), and the specific outcome (status to PENDING and clear error logs). It also distinguishes itself from sibling tools like bulk_reset_phase by focusing on a single node.

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 'allowing a fresh retry from the beginning' implies usage when a task node fails and needs a retry. However, it does not explicitly mention alternatives or when not to use this tool, so it lacks explicit exclusions.

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 adds value by disclosing the atomic write strategy (write-to-temp then rename) to prevent corruption, but it does not mention overwrite behavior, return values, or potential side effects. This is partial but not comprehensive transparency.

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 concise sentence that is front-loaded with the primary action and immediately communicates a key implementation detail. 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?

For a tool with one optional parameter and no output schema, the description covers the core purpose and an important safety detail. It lacks mention of the default file path (though schema provides it) and doesn't state success/failure behavior, but overall it is sufficiently complete for a simple persistence operation.

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 already provides full coverage for the single optional parameter (filePath) with a description and default value. The tool description adds no additional parameter semantics, so 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?

The description clearly states the action ('Persist') and the resource ('current workflow state to disk'), making it unambiguous. It naturally distinguishes from sibling tools like load_graph_state and get_graph_state by specifying write behavior.

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 for saving state but does not explicitly state when to choose it over alternatives or when not to use it. No exclusions or comparisons to load_graph_state or get_graph_state are 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?

No annotations are provided, so the description must disclose side effects. It states it generates files, but it misleadingly implies it derives content from 'provided project requirements' when the schema actually expects pre-written markdown content. It also does not mention overwrite behavior, directory creation, or error handling for the targetDirectory.

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 compact, consisting of two sentences that state the primary function and a key use case. There is no redundant content or unnecessary detail.

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 description provides an adequate overview and usage context, but the mismatch between 'provided project requirements' and the actual content parameters makes it incomplete for an agent to fully understand the tool's behavior. It also does not clarify that parameters are optional and that multiple files may be created, though these are covered in the schema.

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%, providing clear descriptions for all five parameters. The description adds only a high-level grouping (Architecture, Phase-wise Tasks, Test Cases) that maps to the parameters, but does not add significant meaning beyond the schema. This aligns with the baseline of 3.

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 clearly states the tool generates standard project documentation files (Architecture/ER Diagram, Phase-wise Tasks, Test Cases) in the workspace. This specifies the verb (generate), resource (documentation files), and scope (standard types), and it distinguishes itself from sibling graph-management 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?

The description explicitly says it is 'useful for initializing a project plan before creating the graph,' which gives clear context for when to use it relative to sibling tools. It lacks explicit exclusions or alternatives, but the use case is well-defined.

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 discloses a key behavioral trait: enforcing phase gates before execution. This goes beyond simply saying it marks a node, but with no annotations, it still leaves gaps such as what happens on gate failure, whether the action is reversible, or required permissions. The description provides some visibility into the tool's behavior but not comprehensive detail.

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 primary action and state change, then adding the gate condition. Every word earns its place with no redundancy or filler. It is appropriately concise for the tool's simplicity.

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 single parameter and no output schema, the description covers the core action and a critical behavioral constraint (phase gates). It could be more complete by describing failure scenarios or return values, but for a tool of this simplicity, the description provides sufficient context for an agent to invoke it 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?

The input schema already documents nodeId as 'ID of the node to start' with 100% coverage. The description adds no additional parameter semantics beyond what the schema provides, which fits the baseline for full schema coverage. There is no need for further parameter explanation given the single, well-defined 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?

The description uses a specific verb ('Mark') and resource ('task node') with a clear state target ('IN_PROGRESS'), and distinguishes this tool from siblings like update_task_node or reset_task_node by focusing on starting work. It also mentions the phase gate enforcement, which further defines its unique role.

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 implies when to use the tool: to start working on a task node. It also adds that phase gates are enforced, giving a condition for use. However, it does not explicitly state when not to use it or mention alternative tools (e.g., get_ready_tasks) for finding eligible nodes.

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 carry the behavioral burden. It does disclose the not-found behavior (listing available projects), but it does not mention side effects or what 'active context' means for subsequent operations. The behavior is simple enough, but some transparency is missing.

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-loaded with the primary action and followed by a concise behavioral note. No redundant wording; every part 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?

For a single-parameter tool with no output schema and no annotations, the description is adequately complete: it covers purpose, prerequisite, and error behavior. It could be more explicit about the return value or persistence of the switch, but it is not lacking in essential context.

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 describes projectName as 'Exact project name to switch to' (100% coverage). The description adds meaningful context: the project must have been previously initialized, and if not found, a list of projects is shown. This enriches the parameter's meaning beyond the raw 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 action ('Switch the active project context') and the resource ('different project that was previously initialized with init_project_graph'). It also mentions a fallback behavior (listing available projects if not found), which adds specificity and distinguishes it from sibling tools that query state.

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 use case: when you need to change the active project context, and it specifies the prerequisite that the project must have been initialized first. However, it does not explicitly mention alternatives or when not to use this tool, but the context is clear enough given the sibling 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?

With no annotations provided, the description carries the full burden. It discloses a meaningful side effect: re-validation of dependency references and cycle-checks after update. However, it does not mention permissions, potential error outcomes (e.g., if validation fails), reversibility, or any destructive effects, leaving material behavioral gaps for a mutation tool.

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 that front-loads the action and object, then adds the re-validation behavior. Every clause earns its place; zero waste.

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 14 parameters, no annotations, and no output schema, the description is too sparse to be fully complete. It explains the core purpose and validation side-effect but does not describe return values, failure behavior, or how the update interacts with the graph state. The validation mention hints at consequences, but many operational details are missing.

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 very low (14%), with only nodeId having a schema description. The description compensates by naming phase, status, and validation_command, plus a vague 'properties' umbrella, but 14 parameters remain largely undocumented in both schema and description. This is insufficient for an agent to understand the meaning and expected format of fields like tags, depends_on, or acceptance_criteria.

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 ('Update') and resource ('existing task node'), and clearly lists the modifiable scopes: properties, phase, status, or validation command. This distinguishes it from sibling tools like add_task_node (creation) and reset_task_node (reset), especially with the 'existing' qualifier and mention of re-validation after update.

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 for modifying an already-created task node, with the phrase 'existing task node' clarifying when to use it vs. creation tools. It does not explicitly name alternatives or exclusions, but the context is clear enough that an agent would use this over add or reset variants.

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 must carry behavioral disclosure. It reveals atomic sequential state accumulation and race-condition freedom, which are important. But it omits side effects on task state, error behavior, and whether commands are read-only, leaving 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?

The description is a single, dense sentence with no filler. It front-loads the verb and packs essential qualifiers (concurrent, READY/IN_PROGRESS, atomic, race-condition free) 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?

No output schema or annotations mean the description should explain outcomes. It mentions 'state accumulation' but not what is returned, partial failure behavior, or differentiation from validate_task_loop. Adequate for a basic call, but incomplete for an agent to anticipate results.

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 descriptions cover all three parameters, so the baseline is 3. The description adds high-level context (concurrency, task states) but does not enhance per-parameter 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 clearly states the action ('Run validation commands'), the resource ('multiple READY/IN_PROGRESS tasks'), and differentiates from the sibling validate_task_loop by emphasizing parallel execution. It is specific and distinguishes the tool's 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?

It provides clear context: use for multiple READY/IN_PROGRESS tasks concurrently. However, it does not explicitly mention when not to use it or name validate_task_loop as an alternative for sequential validation, so it stops short of full 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?

With no annotations, the description carries the burden of disclosing behavior. It mentions duration tracking, attempt error logging, and live streaming via progress notifications, which adds value. However, it omits critical behaviors: whether the tool modifies graph state, what happens on validation failure, and whether it requires an existing node.

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 long and front-loaded with the primary purpose. Each sentence adds useful context (duration tracking, error logging, streaming) without redundancy or fluff.

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 and annotations, the description must explain return values and side effects. It does not mention what the tool returns, whether it throws exceptions, or how errors are surfaced. The streaming mention is helpful, but the overall completeness is lacking for a command-executing tool with timeout and override options.

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 all parameters with 100% coverage, so the baseline is 3. The description does not add extra meaning beyond the schema, such as how commandOverride interacts with the default validation command or how timeoutMs is used. It does not compensate for missing schema detail, but none 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 description clearly states the tool executes a validation command for a task node, which is a specific verb+resource pairing. It also mentions duration tracking and streaming, which adds context beyond the name. However, it does not explicitly differentiate from sibling validate_parallel_tasks, and the name 'validate_task_loop' is not fully explained.

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 no guidance on when to use this tool versus alternatives like validate_parallel_tasks or start_task. It does not provide any context about when this is the appropriate choice, prerequisites, or situations to avoid.

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