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

With no annotations, the description carries the full behavioral burden, and it discloses almost nothing: whether the operation is read-only, what it returns (a list of framework names? config paths?), how multiple/zero frameworks are handled, or whether it inspects files on disk.

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 tight sentence with the key action and scope front-loaded and no filler. It is appropriately sized, though its brevity is partly the result of omitting useful detail rather than sheer efficiency.

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?

There is no output schema, so the description should explain what detection yields, and there are no annotations to cover safety or side effects. For a tool agents will call before running tests, essential context about the return value and error behavior 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 description coverage is 100%, so the single projectDir parameter (absolute path) is already fully documented in the schema. The description adds no additional semantics about the path, which matches the baseline for high schema coverage.

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

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

The description states a specific action (auto-detect) and resource (test frameworks configured in a project directory), which is far more informative than the vague name 'discover'. It is distinguishable from the run/parse/list siblings, though it never explicitly names 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?

No when-to-use guidance, no prerequisites, and no mention of alternatives among the many test-related siblings (list_runs, run_tests, etc.). Use is only weakly implied by the notion of detecting frameworks before acting on them.

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 does not state that this is a read-only operation, what the returned coverage payload looks like, how large it might be, or how it behaves when coverage was never enabled for the run — significant gaps for a tool with zero annotation 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?

A single front-loaded sentence with no filler or redundancy. It is efficient, though arguably too terse to be appropriately sized for a data-retrieval tool.

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

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

With no output schema and no annotations, the description needs to explain the return shape and preconditions (coverage must have been enabled on the run). It omits both, leaving the agent unable to predict the response or failure modes.

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 parameters (runId and files) are already documented in the schema, making a 3 the baseline. The description adds only the 'previous test run' framing and no extra detail about filtering semantics or runId format beyond what the schema supplies.

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 coverage data') plus a scope qualifier ('from a previous test run'), which separates it from sibling write/run tools like run_tests and rerun_failed. It does not, however, explicitly contrast itself with the closest read siblings (get_failures, get_test_detail), 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?

'From a previous test run' implies it only applies to already-completed runs that had coverage enabled, which is useful context. But there is no explicit when-to-use vs. when-not guidance and no mention of what happens if the run lacked coverage, so usage 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?

No annotations are supplied, so the description carries the full behavioral burden. It usefully discloses that results are enriched with source context around each failure, but says nothing about read-only safety, large-run behavior, pagination, or what happens when a run has no failures.

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?

One sentence, front-loaded with the core action, and the enriching detail (source context) is appended efficiently. No wasted words.

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

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

With no output schema and no annotations, the description is the only source of behavioral and return information. It covers the gist of the returned data but omits the failure record shape, result limits, and error conditions, leaving clear gaps for an agent invoking it.

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 and schema description coverage is 100%, so the schema fully documents 'runId' including its origin from run_tests/run_affected. The description adds no syntax, format, or edge-case meaning beyond the schema, which is the expected baseline.

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 and resource ('Get detailed failure information for a test run') and adds scope with 'including source context around each failure.' It is clearly distinguishable from run_tests or list_runs, though it never explicitly contrasts itself with the closest sibling, get_test_detail.

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, and no named alternative. The phrase 'for a test run' weakly implies it is called after a run, but nothing tells an agent when to prefer this over get_test_detail or rerun_failed.

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 discloses that the response includes a full stack trace, but says nothing about read-only nature, permissions, or what happens for a non-existent test.

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 efficient sentence with the resource and the notable return field front-loaded. Nothing is wasted, though it is arguably too terse to be maximally useful.

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?

There is no output schema, so the description should ideally describe the shape of the returned details beyond the stack trace. With two fully documented required params and no annotations, it is adequate but leaves gaps about the response.

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%, with runId and testName both documented, so the baseline is 3. The description adds no extra semantics such as whether testName accepts fullName vs name ambiguity beyond the schema's own note.

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 ('Get complete details for a single test') and adds the return highlight ('full stack trace'). However, it never names or contrasts with siblings like get_failures or list_runs, so an agent must infer the distinction from the singular 'single test'.

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 explicit when-to-use guidance, no prerequisites, and no mention of alternatives such as get_failures (which surfaces failing tests in bulk). The only signal is the implied 'single test' lookup, which is thin.

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 does not say whether the call is read-only (implied by 'list'), whether results are paginated, what the artifact entries contain, or what authentication the repo/runId require. Only the bare 'list' semantics are conveyed.

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 sentences, front-loaded with the action and resource, with no filler. Slightly terse given the absence of any behavioral detail, 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 two-parameter listing tool with no output schema and no annotations, the description covers purpose and a companion tool but omits return shape (what an artifact entry looks like) and any read-only/auth context. Adequate but with clear 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% and both required parameters (repo, runId) are documented in the schema with format examples. The description adds nothing beyond that, which is the expected baseline 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?

States a specific verb+resource (list artifacts) scoped to a GitHub Actions run, which separates it from list_runs and the parse_* siblings. It does not explicitly name list_runs as the alternative for run-level data, so it falls 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?

The second sentence implies a workflow (use alongside parse_artifact to download and parse test result artifacts), which gives the agent a downstream context. It does not state when to reach for this tool versus list_runs or when artifacts would be absent, so 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?

No annotations are provided, so the description carries the full burden. It implies a read-only listing via 'List', but says nothing about permissions, pagination, ordering, or what a 'summary' omits versus a full run record.

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 purpose front-loaded. It is efficient, though arguably under-specified rather than optimally concise.

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 zero-required-parameter list tool with no output schema, the description is minimally viable but omits what a 'summary' contains and how results are ordered or paginated, which the agent would want when calling it.

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 'limit' parameter is fully documented in the schema, so baseline 3 applies. The description adds only the word 'recent', which mildly implies a default sort order not stated in 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 (List) and resource (recent test run summaries), which is clearer than a tautology. However, it does not differentiate itself from siblings such as get_failures, get_test_detail, or list_artifacts, leaving the agent to infer the boundary.

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 guidance on when to use this tool versus siblings, no mention of prerequisites or exclusions. 'recent' hints at a recency scope but the agent gets no trigger 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 disclosure burden. It usefully reveals that the tool performs a network download from GitHub and which four test-report formats are accepted, which is real behavioral context. However, it is silent on authentication requirements, whether the download is cached, and how malformed or unsupported artifacts are handled.

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 zero filler; the core action is front-loaded and the format enumeration is compressed into a single compact clause.

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?

With no annotations and no output schema, the description should shoulder more of the burden — particularly what the parsed result looks like (a structure? a summary? failures only?) and how it relates to get_failures/get_test_detail. The format list is helpful, but the return contract is left entirely to inference.

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 repo, runId, and artifactName are already documented in the schema, making the baseline 3 appropriate. The description adds only the format-detection behavior, not additional parameter semantics such as whether artifactName is case-sensitive or a glob.

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 two specific verbs (download, parse) against a concrete resource (GitHub Actions artifact) and names the output domain (test results). It implicitly differentiates from siblings like list_artifacts and parse_log, though it never names them explicitly.

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 reach for this tool versus list_artifacts, parse_log, or get_test_detail, nor any stated prerequisite such as needing a prior list call to obtain artifactName. The supported-format list hints at applicability but does not constitute usage routing.

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 behavioral burden, and it does little beyond stating auto-detection. It does not say what happens when detection fails or the log is malformed, whether parsing is deterministic/pure, or what the structured result looks like. For a tool with zero annotation coverage this is a notable 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?

Two tight sentences with zero waste; the core purpose is front-loaded and the framework detail follows naturally.

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?

There is no output schema, so the description should ideally hint at the shape of the extracted results or at least the failure mode for unparseable logs. It covers inputs adequately but leaves the return contract and error behavior unspecified.

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 both parameters are documented inline, including the enum values and the override semantics. The description only restates the auto-detect behavior, adding no syntax or format detail beyond the schema, 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?

States a specific verb (parse) and resource (raw CI/test log text) plus the outcome (extract structured test results), and names the supported frameworks. An agent can tell it apart from the sibling parse_artifact, which implies parsing a stored artifact rather than raw log text.

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 auto-detect default and the force-a-framework escape hatch are stated, which implies when to pass the framework parameter. However, there is no guidance on when to prefer this tool over parse_artifact or how it relates to get_failures/get_test_detail, leaving the selection decision 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 falls short: it does not say whether this creates a new run or mutates the old one, what happens if there are no failures, whether the runId must reference a completed run, or what permissions are needed. For an execution tool that kicks off work, that is a meaningful 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?

A single front-loaded sentence with no filler, and the scoping constraint is stated before any elaboration. Nothing here 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 tool that re-executes tests with no annotations and no output schema, the definition omits the return shape, run-creation semantics, and failure/no-failure behavior. An agent knows the intent but not the mechanics or consequences of calling it.

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 runId and timeout are already documented in the schema; baseline is 3. The description adds no syntax, format, or timeout-unit guidance beyond what the schema already states.

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 ('Re-execute ... tests') plus a scoping qualifier ('only the tests that failed in a previous run'), which cleanly separates it from run_tests and run_affected. It stops short of naming any sibling explicitly, so an agent must infer the boundary rather than being told 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?

The phrase 'in a previous run' implies the trigger condition (a prior run that had failures), but there is no explicit when-to-use statement, no prerequisites, and no mention of alternatives such as get_failures or run_tests for the non-failed case.

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 meaningful behavior beyond the schema: it analyzes the git diff to select test files. It still omits execution side effects (e.g., coverage artifact writes implied by the 'coverage' param), failure semantics, and run duration expectations.

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 sentences with zero filler. The core action and selecting mechanism are front-loaded and nothing is redundant.

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 test-execution tool with no annotations and no output schema, the description is thin on runtime behavior and results. The fully documented schema compensates on the input side, but an agent still lacks context on what execution returns and how failures surface.

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 four parameters (base, timeout, coverage, projectDir) are already documented in the schema. The description adds no additional parameter meaning, which makes the baseline 3 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 states a specific verb ("Run") and resource ("tests affected by git changes") and explains the mechanism ("Analyzes diff to find related test files"). It implicitly differentiates from sibling run_tests by scoping to git-affected tests, but never names run_tests to make the distinction 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 "Run only tests affected by git changes" – an agent can infer this is for incremental/PR-focused runs rather than full suites. However, there is no explicit when-to-use vs run_tests, no guidance on when to prefer a full run, and no note on prerequisites such as a git repository being present.

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 discloses that the result is a compact summary and that failure details require get_failures, which is genuine behavioral context. It omits side-effect information (spawning processes, writing coverage artifacts, the kill-on-timeout behavior) that an agent would want before invoking.

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, front-loaded sentences with no redundancy. The primary action comes first and the routing hint follows immediately; 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?

With no output schema, the description should convey what the compact summary contains and how options like coverage change it. It signals summarization and points to the drill-down tool, which covers the essential workflow, but leaves the shape of the returned summary unspecified.

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 six parameters (projectDir, timeout, coverage, fileGlob, framework, testNamePattern) are already documented in the schema. The description adds no parameter-level meaning beyond that, 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 ('Run tests') plus the return character ('compact summary'), and explicitly names the sibling get_failures for drill-down. It does not differentiate from other run-oriented siblings like run_affected or rerun_failed, 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 second sentence gives useful follow-up routing ('Use get_failures to drill into failures'), which implies this tool is the entry point for a full run. However it never states when to choose this over run_affected, rerun_failed, or discover, nor any prerequisites such as a discovered project setup.

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