squirrelscan

List website issues

list_issues

Read-only

List a website's open audit issues (like a bug tracker: each issue is one failing rule with occurrences across pages, numbered per website). Returns issues sorted by severity. total, returned and has_more describe the issues matching YOUR filters; website_totals (by_status, active_by_severity: open and in_progress) always counts the whole website regardless of filters, so the two can differ (it replaces the earlier severity_summary and status_counts fields). Rows omit the long recommendation (use get_rule with the row's rule_id, or get_issue, or pass include_recommendation: true). Use the issue number with get_issue for full detail and comments. Filter by status/severity/category to narrow down. This is a per-website tracker spanning audits, not a per-run count: one rule failing on 600 pages is ONE issue here, and an issue stays open until an audit re-checks it. So the open count is expected to be far smaller than a run's issues_found (list_audits) or a report's failed+warnings, and the two are not comparable (#1700). To compare runs, use health_score from list_audits.

Input Schema

Name	Required	Description
`limit`	No	Page size (default 50).
`offset`	No	Pagination offset (default 0).
`status`	No	Filter by issue status (omit for all statuses).
`category`	No	Filter by rule category code (e.g. seo, performance, security).
`severity`	No	Filter by severity.
`website_id`	Yes	Website id from list_websites, run_audit, or list_audits.
`include_recommendation`	No	Include each issue's full recommendation text (default false; see get_rule).

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 12, 2026

addedInput schema / additionalProperties
```
Added value: +{}
```

addedInput schema / properties / include_recommendation

Added value: +{
+  "description": "Include each issue's full recommendation text (default false; see get_rule).",
+  "type": "boolean"
+}

Changed3 schema fields changedOct 8, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

removedInput schema / additionalProperties
```
Removed value: -false
```
addedInput schema / properties / offset / maximum
```
Added value: +9007199254740991
```

First observedJul 18, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations only cover the read-only safety profile, and the description adds substantial behavior beyond them: severity sorting, the semantics of total/returned/has_more versus website_totals, the caveat that website_totals ignores filters, and that the long recommendation is omitted by default. The issue-lifecycle explanation (one issue per failing rule, stays open until re-checked) is genuinely useful operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded and most sentences carry non-obvious information (totals semantics, comparability warning). It is dense and long, and the parenthetical noting it 'replaces the earlier severity_summary and status_counts fields' is API-internal detail that does not help an agent decide or call correctly.

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

Completeness5/5

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

For a complex, paginated, filterable tracker with no output schema, the description explains the returned counters, the default field omission, and the counting semantics well enough that an agent understands the response shape and the filters without further documentation.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3, but the description adds real meaning on top: include_recommendation's default-omission behavior and its relationship to get_rule/get_issue, plus the purpose of status/severity/category filters for narrowing. It does not add syntax the schema lacks for limit/offset.

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

Purpose5/5

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

States a specific verb and resource ('List a website's open audit issues') and immediately clarifies the data model ('each issue is one failing rule with occurrences across pages, numbered per website'). It explicitly distinguishes itself from sibling list_audits and per-run counts, so an agent can route correctly without opening schemas.

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

Usage Guidelines5/5

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

Names concrete alternatives and the conditions selecting them: use get_rule / get_issue for the recommendation, get_issue for full detail and comments, list_audits' health_score to compare runs. It also warns that this per-website count is not comparable to a run's issues_found, an explicit when-not.

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

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List website issues

Input Schema

Schema Changelog

TDQS

Glama MCP Gateway

Resources