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

No annotations exist, so the description carries the full burden, and it discloses almost nothing: not what the analysis returns, not whether it is purely heuristic versus grounded in a knowledge base, not the expected size or format of the input, and no limits on error types supported. Only 'suggest troubleshooting steps' hints at the response shape.

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 short lines with the purpose front-loaded and no filler. The Args block largely restates the single schema property, so it earns little of its space, but nothing is bloated.

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, no-annotation, no-output-schema tool, the description covers the minimum needed to call it, but leaves an agent guessing about the nature of the returned analysis and any constraints on input. A sentence on output form and scope would close the gap.

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 0%, but the description supplies an Args block defining error_text as the error message or traceback to investigate, which adds slight meaning over the schema's bare 'Error Text' title by implying full tracebacks are acceptable. It does not specify length limits, encoding, or what detail level produces the best results.

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 (analyze) plus resource (Odoo error) and the added outcome (suggest troubleshooting steps). It is implicitly distinct from the sibling tools, which all inspect modules, manifests, views, models, or security, but the description never makes that separation explicit.

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 the name and the phrase 'error message or traceback to investigate,' so an agent can infer this is the entry point when it has a concrete failure. There is no explicit when-to-use framing, no mention of when a sibling like analyze_odoo_python_model would be the better choice, and no prerequisites.

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; 'using AST' plus 'sandboxed file access' implies a non-mutating static read, and the addon_path wording discloses the sandbox constraint, which is genuinely useful. It still omits what the result looks like (findings list, severity, line numbers), whether the file is ever modified, and what happens when the path is outside the sandbox or does not exist.

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 behavioral summary is front-loaded in a single dense sentence, followed by a conventional Args block. The Args entries largely restate the schema but do add the absolute/relative and sandbox semantics, so the length is close to justified.

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 exists and no annotations are present, so the description should describe the shape of the analysis result and any failure modes; neither is covered. It is adequate for knowing when to call the tool and how to fill both parameters, but incomplete about what comes back.

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 0%, so the Args block does the work: python_path is documented as absolute-or-relative, and addon_path is given a real purpose (containing addon directory that enforces sandboxed access) rather than a bare type. Minor gap: it doesn't say what happens if addon_path and python_path disagree.

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 specific verb ('Analyze') and a precisely scoped resource ('an Odoo Python model file'), then enumerates the defect classes it detects (structural errors, missing attributes, decorator misconfigurations) and the technique (AST). This clearly separates it from siblings such as analyze_odoo_xml_view, validate_odoo_manifest, and inspect_odoo_module without needing to name 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?

The use case is implied by the enumerated error classes, so an agent can infer it should reach for this when statically checking a Python model file. However, there is no explicit when-to-use statement, no exclusion, and no reference to the sibling tools (e.g., inspect_odoo_module or analyze_odoo_error) that an agent might confuse it with.

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 does disclose that addon_path enforces sandboxed file access, which is useful, but it does not state whether the tool only reads files, what permissions are required, or what the analysis returns. This is partially adequate but leaves behavioral 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 front-loads the purpose and checks, then provides a compact Args section. It is appropriately sized with no filler, though the Args formatting is slightly verbose relative to the two parameters.

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 no annotations and no output schema, so the description should explain both operational safety and return behavior. It covers purpose and parameters well but never describes what analyze returns (e.g., list of issues, severity, or success indicator) and gives no explicit sibling routing, leaving an agent without key invocation 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?

Schema description coverage is 0%, so the description must compensate, and it does: file_path is documented as an absolute or relative path to a .csv or .xml security file, and addon_path is documented as an optional containing addon directory used for sandbox enforcement. Both parameters gain meaning beyond the bare 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 (Analyze) and resource (Odoo security file), enumerates the checks (syntax, headers, model prefixes, rules), and names the relevant file types. This distinguishes it from sibling analysis tools that target errors, XML views, Python models, or manifests.

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 use on security files but does not explicitly say when to choose this over inspect_odoo_module, validate_odoo_manifest, or other siblings, nor does it state exclusions. Usage is inferable from the file-type scope, but guidance is not explicit.

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. It does disclose the sandboxing behavior of addon_path ('to enforce sandboxed file access'), which is meaningful context, but it never states that the operation is read-only/non-destructive or what the analysis returns, leaving the safety and output profile undocumented.

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 purpose sentence, then a clean Args block. Every sentence contributes; only minor cost is docstring-style formatting rather than prose, but nothing is wasted.

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 2-parameter analysis tool with no annotations and no output schema, the description covers inputs and the sandbox constraint, but it does not describe the shape of results (e.g., list of issues, severity) or confirm the read-only nature, which an agent needs to use it confidently.

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 0%, so the description must compensate, and it does: xml_path is documented as absolute or relative to the XML file, and addon_path as an optional containing addon directory used to enforce sandboxed access. That adds semantics well beyond the bare string types, though it could still specify accepted formats or path resolution rules.

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?

Uses a specific verb (Analyze) and a specific resource (Odoo XML data or view file), plus enumerates the classes of issues it looks for (structural errors, suspicious references, common issues). It is clearly distinct from analyze_odoo_python_model, validate_odoo_manifest, and analyze_odoo_security by resource type, though it never names a sibling to contrast with.

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 it analyzes but gives no explicit when-to-use, when-not-to-use, or alternative among the many analyze_* siblings. An agent must infer that this is the right tool purely from the resource type 'XML view'.

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 disclosure burden. The word 'static' usefully signals that no code is executed and that this is a read-only inspection, but it says nothing about whether files are touched, whether external services or a live Odoo instance are needed, or how long a full audit takes. It also does not describe the shape of the result (issue list, severity levels, pass/fail), which is important for a 'health' 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 front-loaded: the scope sentence comes first, followed by a clean Args block. It has no filler sentences. The opening sentence is long but still earns its place by enumerating the audited surfaces.

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 two-parameter, annotation-free tool with no output schema, the description covers the inputs well but is silent about the return value. That matters for a 'comprehensive audit' whose usefulness depends on whether it returns structured findings, counts, or prose. It also does not mention any limits or prerequisites.

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 0%, so the description must carry parameter meaning, and it largely does: addon_path is described as an absolute or relative path to the addon directory, and addons_directories is described as an optional list of directories containing other addons, used to resolve module dependencies. The dependency-resolution purpose of the second parameter is genuine added meaning. It does not specify what a relative path is relative to, which is a small gap.

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 specific verb ('Run a comprehensive static health audit') and resource (an entire Odoo addon directory), then enumerates the five areas checked (manifest, dependencies, XML views, Python models, security rules). This makes clear that the tool is a broad, all-in-one audit, unlike the narrow single-aspect sibling analyzers (validate_odoo_manifest, analyze_odoo_xml_view, analyze_odoo_python_model, analyze_odoo_security). However, the description never states this contrast directly, so an agent must infer it.

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 explicit when/when-not guidance or named alternatives. The enumeration of check areas only implies that this tool should be used when a full audit is needed, rather than calling individual sibling analyzers. There is also no mention of when to prefer verify_odoo_live_metadata, which would cover the dynamic side that this static audit does not.

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 behavioral traits. It implies a read-only inspection but does not state return values, error behavior, dependency-checking semantics, or whether the operation 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?

The purpose is front-loaded in a clear sentence, followed by compact parameter documentation. Every part of the description adds necessary information because the schema itself has no property descriptions.

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 is minimally complete for invocation: it explains both required parameters and the basic purpose. However, with no annotations, no output schema, and 0% schema description coverage, it omits return values and dependency-checking behavior, leaving important context 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 0%, but the description compensates well by documenting both parameters: addon_path is the absolute addon directory, and addons_directories is an array of absolute paths to addon-containing directories with examples like standard, enterprise, and custom addons.

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: inspecting an Odoo addon manifest and checking dependencies across addons directories. It is clear what the tool does, though it does not explicitly distinguish itself from siblings like validate_odoo_manifest or check_odoo_addon_health.

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 explicit guidance on when to use this tool versus alternatives such as validate_odoo_manifest or check_odoo_addon_health. Usage is only implied by the purpose statement, leaving the agent to infer 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. It usefully discloses the checks performed (manifest syntax, important fields, data/demo file existence), but does not state that the operation is read-only or describe the validation result shape.

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 compact sentences plus a short Args note; the validation checks are front-loaded and every line adds useful information given the bare schema.

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?

Input semantics are covered, but with no output schema the description should explain what a validation result looks like; it does not. With no annotations and no sibling differentiation, the definition is only adequately complete for 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?

The sole parameter has 0% schema description coverage, and the description compensates by naming it and specifying it is an absolute path to the addon directory. This is sufficient to invoke correctly, though it adds no example path or format detail.

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

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

States a specific verb and resource: validates an Odoo addon manifest plus declared data/demo files. It clearly defines scope, but does not explicitly distinguish itself from siblings such as check_odoo_addon_health or inspect_odoo_module.

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 explicit when-to-use, when-not-to-use, or alternative guidance. An agent can infer it is for manifest validation, but must guess how it differs from sibling tools like check_odoo_addon_health.

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 does useful work by declaring the transport is read-only XML-RPC, that credentials are required, and that the timeout defaults to 10 seconds. It does not say what happens when a model/field is missing (error vs. reported as absent), nor what the response looks like, which matters for a verification call whose whole value is its verdict.

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 core action and the Args block is scannable with no filler. Slightly verbose in the example-heavy parameter lines, but every example disambiguates a format the schema leaves opaque.

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 exists, so the description must characterize the return value and it does not—an agent cannot tell whether it receives booleans per item, a list of missing IDs, or raises on failure. Inputs are fully covered; the result contract is the remaining gap for an 8-parameter verification tool.

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 0%, so the Args block carries the full load and does it well: each of the 8 parameters gets meaning, format, and concrete examples (URL shapes, model names, the fields mapping structure, XML ID samples, timeout default). An agent could construct a correct call from this alone.

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: connect to a live Odoo instance over read-only XML-RPC and verify models, fields, and external XML IDs. That is clearly distinct from the static-analysis siblings, though it never names them explicitly to reinforce the split.

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 'running Odoo instance' and 'dynamically verify' imply this is for live-environment checks rather than static file inspection, but there is no explicit when-to-use guidance, no exclusions, and no reference to the sibling tools that analyze code statically.

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