Plutus

query_events

Read-onlyIdempotent

Query this account's business-event timeline (GitHub releases/PRs, PagerDuty incidents, Jira issues, GitLab, Salesforce onboarding/churn, Stripe subscription created/canceled, Vercel production deploys, Linear issue creation, Sentry newly reported errors) — the same events overlaid on the Cost/Event Explorer charts. Always scope with start_date/end_date: there is no pagination and results are capped at 5000 rows (oldest-first), so an unscoped query over a long history may be silently truncated. Carries no cost figure. Mirrors GET /api/events.

Input Schema

TableJSON Schema

Name	Required	Description
`q`	No	Free-text, case-insensitive substring match against the event title
`end_date`	No	ISO-8601 end of the date range (inclusive)
`meta_repo`	No	Restrict to these GitHub repos (metadata.repo) — only narrows events that carry a repo; events with no repo (e.g. Salesforce onboarding/churn) are unaffected regardless of value
`source_id`	No	Restrict to one event source, e.g. "github", "pagerduty", "jira"
`event_type`	No	Restrict to these event types, e.g. "issue_created", "deploy"
`start_date`	No	ISO-8601 start of the date range (inclusive)

TDQS

A4.9/5.0

Behavior5/5

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

Goes well beyond the readOnly/idempotent/non-destructive annotations by disclosing operational behavior: results are capped at 5000 rows, ordered oldest-first, can be silently truncated without date scoping, and include no cost figure. This is exactly the kind of non-obvious behavior an agent needs to invoke the tool safely.

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

Conciseness5/5

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

Four tight sentences, each earning its place: purpose with source examples, critical scoping caveat, cost distinction, and API reference. No filler or redundant restatement of schema fields.

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 read-only query tool with a fully self-describing schema, the description covers source breadth, filtering expectations, result limits, ordering, truncation risk, and the lack of cost data. The 'Mirrors GET /api/events' reference also gives the agent an external anchor for return behavior without an output schema.

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?

The schema already documents all six parameters with 100% coverage, so the baseline is 3. The description adds meaning for start_date/end_date by explaining why they are essential and linking them to truncation and ordering behavior, which the schema does not convey.

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 ('Query this account's business-event timeline'), enumerates supported event sources, and differentiates itself from cost queries by noting it 'Carries no cost figure.' It also ties itself to the Cost/Event Explorer charts and the GET /api/events endpoint, making its scope unmistakable.

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?

Explicitly instructs the agent to 'Always scope with start_date/end_date' and explains the consequences of not doing so: no pagination, 5000-row cap, and silent truncation. It also provides a clear when-not signal ('Carries no cost figure') and indicates this is the event-timeline query rather than a cost query.

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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TDQS

A3.9/5.0

Disambiguation4/5

Tools are organized by resource (budgets, alerts, anomalies, dashboards, cost tags, recommendations), so most are clearly separable. The cost-tag cluster and the dimension/facet listers are the places where an agent could misselect by name, though descriptions resolve the ambiguity.

Naming Consistency5/5

All tools use snake_case verb_noun names with a clear convention: get_ fetches specific items, list_ enumerates collections, and query_ runs time-bucketed or analytical queries. The pattern holds across all 29 tools with no camelCase or mixed verb styles.

Tool Count2/5

29 tools is well past the typical 3–15 sweet spot and even past the 16–25 heavy band, so the surface feels sprawling despite having few duplicates. Each tool maps to a distinct endpoint, but the sheer number makes it a heavy set for an agent to select from.

Completeness2/5

The read-side is strong: costs, usage, tags, budgets, alerts, anomalies, dashboards, recommendations, and data health are all queryable. However, the surface is almost entirely read-only, and descriptions reference absent tools like create_budget, create_alert_subscription, create_dashboard, set_dashboard_widgets, and delete_dashboard, creating dead ends. That is a significant gap for a cost-management platform.

Resources

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