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Full Stack Trace

boosthis_full_stack_trace
Read-only

One user action stitched across the stack as a waterfall of spans — each with its layer (rn / node / py), code-defined route label, duration, start offset and rating — plus a full-stack score against the shared TTI thresholds, a plain-language summary of where the time went, and slowestLayerRules (rule ids boosthis_get_rule answers for). Spans carry relative durations, offsets and code-defined labels only: never absolute timestamps, source, or user values. A per-install read token is self-scoped, so it answers with that install's own spans; an account_token on the hosted server covers the stitched RN → Node → Python waterfall. Without credentials, or before a trace exists, the answer is a note. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
install_idNoOptional: 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).
read_tokenNoOptional: 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).

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint/destructiveHint annotations, the description discloses that spans carry only relative durations, offsets, and code-defined labels, never absolute timestamps, source, or user values; that a self-scoped token limits visibility to the install; and that absent credentials or a trace the tool returns a note. These are genuine behavioral constraints an agent cannot infer from the schema or 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 dense and front-loads the output shape, then moves to data constraints and credential behavior. It earns its length for a complex tool, but the final 'Read-only.' sentence repeats the annotation and the single long paragraph could be more scannable, so it is not perfect.

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

Completeness4/5

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

With no output schema, the description compensates well by itemizing return fields, data redactions, credential modes, and the no-trace/no-credentials fallback. It slightly loses points because account_token is mentioned without being present in the input schema, and the relationship between install_id/read_token and the hosted account_token is left vague.

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 coverage is 100% and both parameters have thorough descriptions, so a baseline of 3 applies. The description adds value by explaining the consequence of the read_token (self-scoped, returns only that install's spans) and by flagging the hosted account_token path, which is useful beyond the field-level schema text.

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 specifies the resource (a full-stack trace for one user action), the granularity (waterfall of spans with layer, route label, duration, offset, and rating), and the derived outputs (score, summary, slowestLayerRules). This is enough to distinguish it from sibling trace/analysis tools like boosthis_recent_samples or boosthis_session_summary even without an explicit leading imperative verb.

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?

It gives clear operational context: credentials are required, a per-install read token is self-scoped, and missing credentials or no trace yields a note. However, it never states when to prefer this tool over an alternative such as boosthis_recent_samples or boosthis_snapshot, nor names any exclusions beyond missing credentials/trace.

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 concern—alerts, budgets, jobs, promises, rules, crash risk, install/removal—and the descriptions are detailed enough to separate them. A few pairs, like verify_kit/verify_kit_install and recent_samples/session_summary, could be misselected without close reading, but they are not functionally identical.

Naming Consistency3/5

All tools share the boosthis_ prefix and use snake_case, which creates a recognizable namespace. However, the second part mixes noun-only names (alerts, budgets, jobs, snapshot, trend), verb-based names (get_rule, remember_promise, verify_kit), and one sentence-style name (what_should_i_look_at_next), so there is no consistent verb_noun convention.

Tool Count3/5

At 24 tools, this sits squarely in the borderline-heavy range for an MCP server. Each tool does have a distinct role, but the surface feels large, especially with several overlapping read-only diagnostics that could potentially be consolidated.

Completeness4/5

The set covers the main observability lifecycle well: install, verify, monitor, diagnose, check trends, and record promises. Minor gaps exist—like no way to mutate alert states or delete promises through the MCP—but these appear intentional and are documented as dashboard-side actions.

Resources