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Glama

Boosthis

by com.boosthis

Full Stack Trace

boosthis_full_stack_trace
Read-only

One user action across the stack as a nested waterfall of spans (layer, route label, duration, start offset, rating), each under the call that caused it; criticalHop names the hop responsible for the end-to-end time, not just the longest. Relative timings, code-defined labels only. A read token sees one install; account_token the whole chain. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trace_idNoOne trace by id (32 hex, from the trace page). Absent: the latest.
install_idNoInstall id (dashboard card).
read_tokenNoRead-only token, same card.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • changedInput schema / properties / install_id / description
      Previous value: -"Install id, from the dashboard card."New value: +"Install id (dashboard card)."
    • addedInput schema / properties / trace_id
      Added value: +{
+  "description": "One trace by id (32 hex, from the trace page). Absent: the latest.",
+  "type": "string"
+}
  2. Changed2 schema fields changed
    • changedInput schema / properties / install_id / description
      Previous value: -"Install id, from the project's dashboard card."New value: +"Install id, from the dashboard card."
    • changedInput schema / properties / read_token / description
      Previous value: -"Read-only token for it, from the same card."New value: +"Read-only token, same card."
  3. Changed2 schema fields changed
    • changedInput schema / properties / install_id / description
      Previous value: -"Optional: the install id to read live data for. On the HOSTED Boosthis MCP, copy it from the in-app dashboard's \"Connect your AI\" card and pass it here. Omit on a local stdio server (it uses BOOSTHIS_INSTALL_ID from the env)."New value: +"Install id, from the project's dashboard card."
    • changedInput schema / properties / read_token / description
      Previous value: -"Optional: the SELF-scoped read token for that install (paired with install_id). It is read-only — it can read this app's own perf data but CANNOT delete it. Copy it from the in-app dashboard. Omit on a local stdio server (it uses BOOSTHIS_READ_TOKEN from the env)."New value: +"Read-only token for it, from the same card."
  4. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare read-only, and the description reinforces it while adding material behavior beyond the annotations: waterfall nesting, relative timings, code-defined labels, criticalHop semantics, and token-based install vs whole-chain visibility. No contradictions.

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?

Two dense sentences, front-loaded with the core output shape, then constraints and scope. Every clause carries information, with no filler.

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 carries the return-format burden and satisfies it: span fields, nesting rule, criticalHop naming, relative timings, label origin, and auth scoping are all disclosed. The tool is simple enough that nothing else is needed for correct invocation.

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 covers all three parameters, so baseline is 3. The description adds useful semantics: trace_id is optional and defaults to latest, and read_token scopes visibility to one install instead of the whole account chain. This goes beyond the schema's field-level help.

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 precisely defines the resource: one user action displayed as a nested waterfall of spans, with explicit span fields and the criticalHop extension. It is clearly distinguishable from sibling tools like session_summary or trend even without naming them.

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 intended use case is implied by 'one user action across the stack,' but there is no explicit statement of when to choose this tool over related siblings or exclusions for cases like multiple actions or aggregate views. No alternatives are named.

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

Most tools target a distinct resource or workflow: alerts, budgets, crashes, traces, jobs, promises, kits, and rules. A few summary-style tools such as snapshot, session_summary, and what_should_i_look_at_next overlap in spirit, but their descriptions clarify the different aggregation levels and purposes.

Naming Consistency4/5

All tools share the consistent boosthis_ snake_case prefix, making the family immediately recognizable and predictable. However, naming mixes noun-resource styles with verb-command styles, and a few names are question-like phrases such as boosthis_what_should_i_look_at_next and boosthis_which_kits.

Tool Count3/5

At 26 tools, this is on the heavy side and slightly past the 16-25 range where a large toolset starts to feel burdensome. The count is defensible because each tool maps to a distinct observability or kit-management concern, but agents will need to do significant selection work.

Completeness4/5

The surface covers a broad lifecycle: kit installation and verification, rules and code matching, performance snapshots and trends, crash risk, release checks, promises, alerts, and connection status. It is mostly read-only by design, so the lack of write operations beyond remember_promise is not a major gap, though alert and job management actions are intentionally absent.

Resources