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appcircleio

appcircle-mcp

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by appcircleio

get_build_insights_report

Compute an aggregated Build Insights Report from Appcircle build history, covering health snapshot, root cause, artifact health, workflow quality, queue time, and maturity assessment, with automatic handling of incomplete data.

Instructions

Get a computed Build Insights Report over build history: Health Snapshot + Trends, Root Cause, Artifact Health, Workflow Quality, Queue Time, and Maturity Assessment analysis, aggregated server-side.

Unlike get_build_history_report (which returns raw paginated records), this tool fetches every page internally, computes percentiles/grouping/MTTR/flaky detection in Python, and returns only the small aggregated result. Sections that can't be computed from the available data (e.g. a field stripped by an Appcircle role restriction) are omitted rather than rendered as zeros or fabricated, and flagged in meta.omitted_sections / meta.omitted_subsections. Only the current-period build history fetch is mandatory -- every other fetch (previous period, profiles, queue waiting, signing identities, per-profile workflow/trigger/configuration data) is best-effort: a 401/403 from a token lacking permission for that specific resource (e.g. an admin-only endpoint) omits just the dependent section/subsection instead of failing the whole call, and is listed in meta.failed_fetches.

A main-org access token sees build history spanning every sub-organization, but can only enumerate its own org's profiles (the Appcircle API itself enforces this -- not something this tool can fetch around). By default the report is scoped to the token's own organization: build records whose profile isn't in that token's own profile list are excluded before any section is computed, so every section always means the same scope. Set include_sub_orgs=True to keep cross-org records in history-derived metrics (Health Snapshot, Root Cause, Artifact Health, Speed/Reliability) -- Workflow Quality/Discipline/Security for those profiles still can't be resolved (the API limitation doesn't go away), so they're omitted for those specific profiles rather than fabricated, and listed in meta.unresolved_profiles. queue_time has no profile field to scope by, so it's always a tree-wide aggregate regardless of this flag.

Args: start_date: Optional start date (format: "YYYY-MM-DD") for the current period. end_date: Optional end date (format: "YYYY-MM-DD") for the current period. If both start_date and end_date are omitted, defaults to the last 30 days. If only one is given, the other is filled to a 30-day-wide window. sections: Optional list of sections to compute. Subset of ["health_snapshot", "root_cause", "artifact_health", "workflow_quality", "queue_time", "maturity_assessment"]. Defaults to all six. Invalid section names return a validation error. include_sub_orgs: If True, keep cross-org build records in history-derived metrics instead of filtering them to the token's own org (default False). See the note above on what stays unresolved either way.

Returns: Standard envelope (see docs/tool_contract.md): - Success: success (true), data (date_range, sections.health_snapshot, sections.root_cause, sections.artifact_health, sections.workflow_quality, sections.queue_time, sections.maturity_assessment), meta (requested_sections, omitted_sections, omitted_subsections, failed_fetches, cross_org_builds_excluded, unresolved_profiles). - Error: success (false), error (tool, type, message, details).

Examples: Full report, last 30 days: get_build_insights_report() Root cause only, custom range: get_build_insights_report( start_date="2026-01-01", end_date="2026-01-31", sections=["root_cause"] ) Include cross-org records from a main-org token: get_build_insights_report(include_sub_orgs=True)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
sectionsNo
start_dateNo
include_sub_orgsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description carries full burden and excels. It discloses internal fetching, computation, best-effort behavior for fetches that fail due to permissions, omission of unresolvable sections rather than fabrication, cross-org scoping nuances, and detailed meta fields for omissions and failures. This level of transparency is exemplary.

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?

The description is well-structured with a summary, contrast, behavioral notes, Args, Returns, and Examples. It is front-loaded with purpose. However, it is somewhat verbose and could be tightened while retaining completeness.

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?

The description is exceptionally complete for a complex tool, covering input parameters, behavioral nuances (permissions, cross-org, best-effort), output structure with meta fields, and examples. With no output schema provided, the Returns section sufficiently describes the result format.

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

Parameters5/5

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

Given that the input schema has 0% description coverage, the description fully compensates with a detailed Args block explaining each parameter's format, defaults, behavior, and valid enum values (for sections). This adds complete meaning beyond the schema's type information.

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?

The description clearly states it 'Get a computed Build Insights Report over build history' and enumerates the sections computed. It explicitly distinguishes itself from the sibling 'get_build_history_report' which returns raw paginated records, providing clear differentiation.

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?

The description explains when to use this tool versus alternatives, specifically contrasting with get_build_history_report. It also provides detailed guidance on the include_sub_orgs flag, default date ranges, and how sections are handled, giving the agent clear decision criteria.

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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