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 usefully discloses a default outcome ('cells are visible in the UI by default'), but says nothing about session binding/auth requirements, whether the cell is persisted or executed, or what occurs if both after and before are supplied.

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 with no filler, and the default-behavior point is front-loaded. The opening sentence largely restates the name/title, which is conventional but not additive, keeping it just below a 5.

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?

An output schema exists, so return values need not be described, and the schema fully covers parameters. However, for a creation tool with no annotations, the description omits permission/session prerequisites and the interaction between the mutually related after/before placement options, leaving meaningful gaps.

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 all seven parameters are already documented in the schema; this sets the baseline at 3. The description adds a modest amount of meaning for hide_code by explaining the intent behind the flag, but nothing for name, after, before, server_url, or session_id.

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 ('Create a new cell in the notebook'), which cleanly separates it from siblings like edit_cell, delete_cell, and run_cell. It does not explicitly name those siblings or clarify boundaries, but the create/edit/delete/run distinction is unambiguous from the verb alone.

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 gives real guidance for one decision point: hide_code defaults to False, and True is for 'setup/implementation cells you want hidden.' That is usage guidance for a parameter rather than for the tool itself; there is no guidance on when to use create_cell versus edit_cell, or on the after/before positioning options.

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 behavioral burden. 'Delete' implies a destructive mutation, but the description does not state whether deletion is permanent, reversible, requires specific permissions, or affects dependent cells. It adds little beyond the operation 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 efficient sentence with no wasted words and the action is front-loaded. It is appropriately concise, though for a destructive operation it could benefit from one more sentence of context without becoming verbose.

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 a destructive tool with no annotations, no stated reversibility or permissions, and alternatives among siblings, the description is insufficiently complete. While the output schema exists and parameters are fully documented in the schema, the lack of any behavioral or safety context leaves an agent without critical information 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%, so the input schema already documents all three parameters (cell_id, server_url, session_id) with descriptions. The tool description adds no additional meaning about parameter usage or formats. The baseline of 3 is appropriate when 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 states a specific verb and resource: 'Delete an existing cell from the notebook.' It is clear what the tool does. However, it does not explicitly differentiate itself from siblings like edit_cell or create_cell beyond the obvious verb, 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 description provides no guidance on when to use this tool versus alternatives such as edit_cell or create_cell. There are no exclusions, prerequisites, or contextual triggers mentioned. It only states the action, leaving usage entirely to inference.

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

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

With no annotations, the description carries the full burden and does it well: it discloses the staleness guard, the two refusal conditions, and the purpose (preventing silent overwrite of a concurrent edit). It stops short of describing permission/auth requirements or what a successful edit returns, but the guard disclosure is substantial behavioral 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?

Front-loaded with the core action, then the guard explained in two tight sentences with no filler. The parenthetical callout of needs_read/conflict is economical and information-dense.

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 mutation tool with 7 params, an output schema, and full schema coverage, the description supplies the critical non-obvious behavior (the freshness guard) that the schema alone would hide. Minor gaps remain around session requirements and success semantics, but they are largely covered by structured fields.

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, but the description adds real meaning for check_fresh beyond the schema's one-liner by spelling out the two staleness failure modes. The remaining parameters (name, hide_code, source, session_id) are left entirely to 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?

States a specific verb and resource ('Edit an existing cell's source code') and implicitly separates itself from create_cell/delete_cell/run_cell. The guard discussion further delineates it by naming get_cell_data and get_cell_map as related-but-different operations, so an agent can place it precisely among siblings.

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 the edit proceeds and when it is refused (needs_read with no read baseline, conflict when source changed), plus the check_fresh=False escape hatch. It also tells the agent how to satisfy the precondition (use get_cell_data, not a get_cell_map preview), which is genuine routing 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 full burden, and it does disclose genuinely non-obvious behavior: empty cell_ids returns all cells, and unresolvable ids surface in missing_cell_ids instead of being silently dropped. The rationale (write tools refuse absent ids, so silence would hide the mistake) adds real context. It omits cost/pagination implications of fetching all cells, so it is not fully complete.

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?

Purpose is front-loaded in sentence one, followed by scope, then the edge-case semantics. The final explanatory clause is slightly long but earns its place by justifying the missing_cell_ids design. No filler sentences.

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?

An output schema exists, so the description needn't explain return shapes, and it covers the default/all-cells case plus the error-reporting edge case. The remaining gap is disambiguation from the closely related read siblings, which a three-parameter read tool in this family would benefit from.

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 schema already documents cell_ids semantics, the accepted string/array/null shapes, server_url, and session_id. The description restates the empty-equals-all behavior without adding new format or constraint detail, so the baseline 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 first line gives a specific verb and resource ("Get full runtime data for one or more cells") and enumerates what 'runtime data' means (source code, errors, variables). It does not, however, distinguish itself from siblings that overlap heavily with that content — get_errors, get_variables, and get_cell_outputs are adjacent tools and the description never says how this differs from them.

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

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

Usage is only implied: the empty-cell_ids behavior tells the agent this can be used as a bulk fetch, but there is no statement of when to prefer this over get_cell_map, get_errors, or get_variables. No exclusions, prerequisites, or alternatives are named.

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, and it discloses a genuinely non-obvious behavior: a preview does not record the edit_cell read baseline and only updates this tool's own change-detection snapshot. That is valuable. It still omits other behavioral context such as how the snapshot interacts across sessions or whether the map is cached, so it falls just short of full coverage.

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?

Front-loaded with the core action and return contents in two short sentences, followed by one earned cautionary paragraph about the edit baseline. 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?

An output schema exists, so return format need not be explained, yet the description still summarizes it. Combined with the preview/edit-baseline caveat and clear routing to get_cell_data, an agent has everything needed to call this 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?

Schema description coverage is 100%, so server_url, session_id, and preview_lines are already documented in the schema. The description adds no extra semantics about these parameters (e.g., preview_lines tradeoffs), so the baseline 3 applies.

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

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

The description names a specific verb+resource (get a map of cells) and states exactly what it returns: cell IDs, names, code previews, and runtime state. It also positions itself against the sibling get_cell_data by calling itself the 'starting point for navigating a notebook' and contrasting previews with full source.

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 states when to use it ('starting point for navigating a notebook') and names the alternative with a condition: read full source with get_cell_data before editing. The agent does not need to infer the routing decision.

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 exist, so the description carries the full burden. It does disclose one genuinely useful non-obvious behavior — unresolved IDs surface in missing_cell_ids so an empty cell is distinguishable from a nonexistent one — but says nothing about output size limits, truncation, pagination, or whether retrieval has side effects.

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-loading the core purpose before the edge-case note, with no filler. The second sentence is slightly roundabout in phrasing but every clause adds 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?

An output schema exists, so return values need not be explained, and all three parameters are schema-documented. The missing-id behavior is covered; the only gap is guidance on selecting this tool over sibling readers and any limits on output volume.

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 cell_ids, server_url, and session_id are already fully documented in the schema. The description adds no semantics on top of that (it does not even restate the empty-means-all-cells default), 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?

States a specific verb and resource (get cell execution outputs) and enumerates what those outputs contain (visual display, console streams). It does not name or contrast with the nearest siblings (get_errors, get_cell_data, run_cell), so an agent must infer the boundary itself.

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 says what is retrievable but never states when to call this instead of get_cell_data or get_errors, nor any prerequisite such as having run the cell first. Usage is only implied by the resource name.

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, and it does disclose one meaningful trait: the graph is always full-notebook and cannot be scoped. It says nothing about permissions, cost/latency on large notebooks, or failure modes, leaving real gaps for a graph-traversal read.

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 short sentences, front-loaded with the core purpose, and the trailing 'always FULL notebook graph' caveat is placed after the content list where it belongs. Minor cost: the second sentence is a dense enumeration that could be trimmed without losing much.

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?

An output schema exists, so return values need not be explained, and all four parameters are documented in the schema. What remains missing is the usage layer: no stated preconditions (active session/server_url binding) and no guidance on choosing this tool over get_variables, which is the main decision an agent faces here.

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 two non-trivial parameters (depth, cell_id) already carry explicit NOT IMPLEMENTED refusal notes in the schema. The description adds no parameter-level meaning, so the baseline 3 for high schema coverage applies even though the description's 'always FULL graph' line loosely reinforces why those args are refused.

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 first sentence names a specific verb and resource ('Get the cell dependency graph') and the second enumerates the actual content (variable relationships, parent/child edges, ownership, cycles). That materially separates it from get_variables or get_cell_map, but no sibling is named explicitly, so an agent must infer the boundary from the content list alone.

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

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

There is no when-to-use statement, no prerequisite (e.g. active session required), and no routing to alternatives such as get_variables for a flat variable list. The only usable cue is the implicit 'always the FULL notebook graph' constraint, which hints at when not to bother with scoping rather than when to call the tool.

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

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

With no annotations, the description carries full disclosure and does so well: it explains that two channels (structured_errors, console_stderr) are never conflated, that stderr tracebacks surface even when the structured channel is empty, and that has_errors/total_errors are structured-only backward-compatible counts. This is meaningful behavioral context beyond structured fields. It stops short of describing side effects or cost, though for a read-only diagnostic tool that gap is minor.

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 opening sentence front-loads the purpose, and the channel breakdown is organized and to the point. It is somewhat dense with parenthetical field lists, but every clause conveys distinct semantics rather than 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?

An output schema exists, so return values need not be explained, yet the description still clarifies the non-obvious semantics of the count fields and channel separation. The main omission is guidance on how this differs from lint_notebook when an agent is troubleshooting.

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 server_url and session_id are already documented in the schema, including their optional-if-bound behavior. The description adds no parameter meaning, which is acceptable at full coverage but not additive.

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 all errors in the notebook session, organized by cell') and immediately scopes what is returned. It does not explicitly differentiate itself from the sibling lint_notebook, leaving the agent to infer the static-vs-runtime distinction.

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 never says when to reach for this tool versus alternatives such as lint_notebook or get_cell_outputs. It references get_cell_outputs only to describe a shared output shape, not to route the agent, and offers no prerequisites or exclusion conditions.

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

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

With no annotations, the description carries the full behavioral burden and does disclose a genuinely non-obvious trait: empty variable_names returns the notebook's own session names with the inspection template's scaffolding excluded, since the scratchpad shares the kernel namespace. 'Get' implies a read-only operation, and return values are covered by the output schema, so the remaining gap is minor.

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 sentences, front-loaded with the core purpose and then the empty-argument semantics. The parenthetical scaffolding explanation earns its place, though the phrasing is slightly dense.

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?

An output schema exists, so return format need not be described, and the read-only nature is implied. The description covers purpose, scoping behavior, and the empty-argument case, leaving little an agent needs that is 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 coverage is 100%, establishing a baseline of 3, and the description adds meaning beyond the schema by explaining what 'empty' actually returns — the notebook's own names minus template scaffolding — which the schema's bare 'Empty = all' does not convey.

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+resource: 'Get tables and variables information in the session,' and clarifies it returns kernel variables and DataFrames. It is clearly distinguishable from sibling cell/error tools, though it never explicitly names an alternative for contrast.

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 by context ('in the session', inspecting kernel state), but there is no explicit when-to-use guidance and no exclusions relative to siblings like get_cell_outputs or get_dependency_graph. An agent can infer intent but is not directed.

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 load. It usefully discloses that this is the same engine behind 'marimo check' and enumerates breaking/runtime/formatting categories, which conveys the nature of the output. But it never states whether the tool only reports or also mutates the notebook, nor that an active session/server is required — relevant given sibling set_active_session and the optional server_url/session_id params.

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?

Front-loaded with the core action in the first sentence, followed by a compact categorized bullet list. No filler, though the 'marimo check' aside is slightly redundant with the engine statement.

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?

An output schema exists, so return-value explanation is unnecessary, and the three issue categories give a good sense of what comes back. What's missing is the read-vs-write nature of the operation and session requirements, which the schema only partly covers.

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 optional params (server_url, session_id) are already fully documented in the schema, including their fallback to bound values. Baseline 3 applies; the description adds nothing about parameters.

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 ('Lint a marimo notebook') and enumerates the three issue classes it detects. It does not, however, differentiate itself from the sibling get_errors, which an agent might reasonably confuse with linting output.

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

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

There is no guidance on when to lint versus when to call get_errors, run_cell, or any other diagnostic sibling, and no stated preconditions. The 'marimo check' reference gives provenance but not a usage condition.

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 and meets it: it discloses server-side binding state, how that state is keyed (MCP session identity), and the non-obvious client-dependent caveat that makes the binding unreliable. This is exactly the kind of stateful side effect an agent could not infer from the name 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?

Purpose is front-loaded in a single short sentence, followed by return contents and then the binding caveat. The third paragraph is dense and version-specific, but each sentence carries load-bearing information about when the binding fails, so the length is justified rather than padding.

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?

An output schema exists, so return values need not be explained, yet the description briefly summarizes them (file paths and session IDs). Combined with the binding semantics and the client caveat, an agent has everything needed to call this correctly and to know what happens on the next call.

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 there is only one optional parameter, so the baseline is 3. The description earns an extra point by explaining the behavioral consequence of omitting `server_url` — it ties omission to the auto-binding of the first discovered session, which the schema's "discovers servers from the marimo registry" note does not convey.

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 first sentence names a specific verb and resource ("List currently active marimo notebooks") and is the only discovery/listing tool among siblings dominated by cell/notebook mutation and inspection tools. An agent can distinguish it immediately without opening the schema.

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 states the calling pattern explicitly: the first discovered session is auto-bound, so subsequent calls may omit `session_id` and `server_url`. It goes further and names the condition under which that optimization fails (fastmcp's own Client on pinned fastmcp 4.0.3 negotiating a new MCP session per request), telling the agent exactly when to pass both parameters explicitly.

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 behavioral burden. It says nothing about side effects (state mutation in the notebook, execution ordering, whether it blocks), authentication needs, or the session-binding requirement hinted at in the schema. 'Run' implies execution but no consequences are disclosed.

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 short sentence with no waste and the key action front-loaded. It is efficient, though arguably too terse given the tool's execution side effects.

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?

An output schema exists so return values need not be described, but for a state-mutating execution tool with zero annotations the description is inadequate. It omits side effects, session requirements, and any interaction with output-retrieval siblings, leaving meaningful gaps.

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 all three parameters (cell_id, server_url, session_id) are already documented in the schema. The description adds nothing beyond the schema, which is the baseline 3 for high 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 gives a clear verb+resource ('Run (execute) an existing cell'), which distinguishes it from create_cell, edit_cell, and delete_cell by action. However, it does not differentiate it from other read/observation siblings like get_cell_outputs or get_cell_data, leaving the scope slightly ambiguous.

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

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

There is no guidance on when to use this tool versus alternatives, no mention that running a cell is the prerequisite for retrieving outputs via get_cell_outputs, and no indication of session prerequisites. The agent must infer all usage 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, the description carries the full burden and does so: it discloses where the binding is written (MCP-session state plus process-global fallback), how stdio vs HTTP/SSE differ, and that ambiguous argument-less calls are refused with reason: binding_ambiguous rather than leaking another client's notebook. That is exactly the non-obvious behavior an agent needs.

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 purpose is front-loaded in the first sentence and every subsequent sentence carries behavioral detail, but the middle block is a dense wall of text mixing stdio/HTTP semantics that could be split for faster scanning. Not wasteful, just heavy.

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?

An output schema exists so return values needn't be described. Given the tool's deceptively stateful nature and lack of annotations, the description covers the persistence model, fallback scope, and failure mode thoroughly — nothing essential to calling it correctly is 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 coverage is 100%, so baseline is 3, but the description adds real meaning beyond the schema: that session_id and server_url become omittable in later calls because the binding persists, and why server_url is optionally bound alongside. This exceeds the schema's per-field text.

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 ('Set the active notebook session') and scopes the effect to 'subsequent tool calls', which cleanly separates it from siblings like list_active_notebooks or get_cell_map. An agent can tell what state this mutates without opening the schema.

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 routes the agent to list_active_notebooks first to discover sessions and their IDs, and tells it to pass both arguments explicitly in the multi-client HTTP/SSE case. It lacks an explicit 'when not to use' framing, but the conditional guidance is unusually concrete.

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?

Adds substantial behavior beyond the annotations: the update triggers reactive re-execution like a user interaction, is flushed on code-mode context exit, and values are verified by read-back so 'status: ok' with 'verified: true' means the value actually moved. It also discloses the refusal path (shape mismatch rejected before applying, corrected payload in did_you_mean) and that rejected values are never reported as success.

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?

Front-loaded with the one-line purpose, then layered detail in descending priority (type constraint, value shapes, then execution/verification semantics). It is dense and multi-paragraph but nearly every sentence carries non-redundant information; the value-shape enumeration is long but earns its space.

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 mutating tool with a live output schema, it covers everything an agent needs: preconditions, value shapes, error/refusal behavior, timing of the flush, and the meaning of the verification fields. The session-binding caveat is delegated to the session_id schema and list_active_notebooks, which is coherent.

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, but the description adds real per-parameter meaning: 'value' shape is enumerated per widget type (scalar for slider/text, one-element list for dropdown, list of keys for multiselect, two-element list for range_slider, bool for checkbox) and is never coerced. The server_url/session_id parameters are left to the schema, which already documents them.

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?

Opens with a specific verb+resource+scope: 'Set the value of a live marimo UI element, by its variable name.' It immediately distinguishes itself from the cell-editing siblings by stating it accepts no source code, so an agent can tell it apart from edit_cell/run_cell without opening either schema.

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?

Gives a clear precondition (the kernel global must resolve to a marimo UI element, with examples of types) and an explicit when-not ('NO source code … not for arbitrary code execution'), which routes the agent away from misuse. It does not name a sibling alternative for the code-execution case, so it stops short of full when/when-not/alternatives.

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