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FeatureBoard MCP Server

by valentil

Agent monitor v2 (live sessions, stalls, spend)

get_agent_monitor
Read-only

Monitor in-progress tickets, showing elapsed time, stall status, token spend, and orchestration details to catch stuck tickets.

Instructions

Live snapshot of the board's currently-running work: every In Progress ticket with elapsed time since it went In Progress (from the ticket_events.jsonl audit log, falling back to its earliest work-log entry or createdDate when there's no recorded status event), its last event (most recent audit event or work-log entry, whichever is newer) with age, token spend so far vs its cap: label and the resulting spend ratio, and a stalled flag (no event/work-log activity within stallMinutes, default 30). Also reports costSoFar and capCost in dollars (via project-config-overridable pricing; capCost is null when no model can be inferred for the ticket). Each ticket also carries lastDispatch ({worker, model, parallel, note, ageMinutes}, null if record_dispatch was never called for it) — who's actively working it, a sub-agent or the orchestrator — so the board can render an orchestration chip without a separate call. Sorted most-recently-active first, with a top-level summary (count, stalledCount, subAgentCount, parallelCount, totalSpend, totalCap, totalCostSoFar, totalCapCost, stalledTickets). Pairs with churn mode: a stalled ticket mid-churn usually means the agent is stuck or has gone quiet. Use it to see what's underway, who/what is running it, and catch stuck tickets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asOfNoReference time (ISO) to measure elapsed/idle against; defaults to now.
projectYes
stallHoursNoDeprecated alias for stallMinutes (converted to minutes); ignored if stallMinutes is given.
stallMinutesNoInactivity minutes after which an In Progress ticket is flagged stalled. Defaults to 30.
Behavior5/5

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

Annotations provide readOnlyHint=true, and the description adds extensive behavioral details: fallback logic for elapsed time, last event age calculation, token spend ratio, stalled flag definition, lastDispatch structure, and summary aggregation. No contradictions with annotations.

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 lengthy but efficiently packed with details, front-loaded with purpose. Each sentence adds value, though it could be slightly more concise without losing meaning.

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?

With no output schema, the description fully explains the return format: each ticket's fields, lastDispatch object, summary statistics, and special cases (capCost null). Annotations are present. Complete for the tool's complexity.

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

Parameters3/5

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

Schema description coverage is 75% (3 of 4 parameters described). The description does not add new semantic info for parameters beyond the schema, except reinforcing stallMinutes default and context. Baseline 3 is appropriate.

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 states 'Live snapshot of the board's currently-running work: every In Progress ticket with elapsed time...' clearly defining the tool's purpose. It distinguishes itself from sibling tools like get_board or get_task by focusing on agent monitoring metrics.

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

Usage Guidelines3/5

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

The description implies usage ('Use it to see what's underway...') and mentions pairing with churn mode, but does not explicitly state when not to use it or compare to alternatives like get_live_activity.

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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