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

Annotations cover safety (readOnly, idempotent, non-destructive), so the bar is lower, and the description adds meaningful behavioral context beyond them: it explains the data source precedence (AGENTHUB_STATE_FILE vs in-memory) and, crucially, that in-memory returns are flagged with is_sample_data=true. That is a non-obvious trait an agent needs to trust the output.

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 tight sentences. The primary behavior (return pipeline state as JSON) is front-loaded, with the data-source nuance following. Every clause earns its place.

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

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

For a zero-param read tool with strong annotations and no output schema, the description covers behavior and the sample-data caveat well. The one gap is the absence of any routing guidance versus the sibling status/monitor tools.

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?

Zero parameters, so the baseline is 4. The description correctly implies no input is needed and instead explains the environment variable that governs behavior, adding value where there is no schema surface to document.

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+resource: return the current pipeline state as structured JSON. It distinguishes itself from trigger_action (mutation) by being a read. However it does not explicitly name a sibling, so it stops short of full sibling differentiation.

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?

No when-to-use vs alternatives guidance. It doesn't mention show_agenthub_monitor, which is the obvious sibling an agent might confuse this with, nor does it say when this tool is preferable. Usage must be inferred.

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 the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds genuinely useful behavioral context beyond that: it renders inline in the host, reads from a configured state file, and falls back to built-in sample data when none is configured. This fallback disclosure is exactly the kind of trait annotations cannot express.

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 tightly written sentences with the action verb front-loaded and zero redundant content. Every clause earns its place by adding either the render target or the data-source behavior.

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 read-only, single-optional-parameter dashboard tool with no output schema, the definition covers purpose, render location, and data sourcing. Annotations handle the safety profile. Only the absence of any sibling-routing guidance keeps it from being fully complete.

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

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

Schema description coverage is 100% and the single 'view' parameter is fully documented in the schema, including its enum and default. The description adds no information about the view mode, 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 uses a specific verb ('Render') plus a specific resource ('interactive pipeline dashboard inline in the host') and even names the data source (configured state file or built-in sample data). This is clear and specific, but it does not explicitly differentiate itself from siblings like get_status or trigger_action, so it falls short of a 5.

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

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

The phrase 'inline in the host' implies this is a visual rendering tool rather than a data-fetching tool, which hints at when to use it over get_status. However, there is no explicit when-to-use guidance, no stated alternatives, and no exclusions, so the guidance is only implied.

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 the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=false). The description adds genuine value beyond that by clarifying the side effect is limited to in-memory state and that no commands are executed, no jobs started, no network reached. It does not cover permissions or retention of the recorded state, keeping it short of a 5.

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, zero filler, and the core side-effect ('record an action request ... return the updated state') is front-loaded. The second sentence exists solely to prevent a common misreading (that this executes something), so it earns its place.

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

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

For a one-parameter tool with no output schema, the description supplies everything an agent needs: what is recorded, what is mutated, what is returned, and what is explicitly not done. The absence of an output schema is compensated by the stated return value ('the updated state').

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

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

There is a single parameter, fully documented by the schema (100% coverage) with an enumerated value set, so the schema carries the semantics. The description adds nothing about the meaning of the individual enum values (run-dag, run-harness, run-diff), which is the minimum viable baseline for a fully-covered single param.

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

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

The description states a specific verb and resource: it records an action request into the server's in-memory state and returns the updated state. An agent immediately understands this is a state-annotation tool, not an executor. It does not explicitly name or contrast with the siblings (get_status, show_agenthub_monitor), so it stops short of full sibling differentiation.

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

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

Usage is implied rather than stated: an agent can infer it should call this when it wants the dashboard to reflect a requested action, but there is no explicit when-to-use versus when-not, nor any reference to the sibling tools. The 'does not execute commands' note sets expectations for the caller but is not a selection guideline.

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