preflight

Get context window efficiency metrics: unique vs. repeated file reads, repeated-read ratio, and top re-read files. A high ratio suggests the model is losing context.

Get p50/p95/p99 latency percentiles for tool calls, broken down by tool type. Use to identify which tools are slowest in the current session.

Get task lifecycle metrics: completed task count, average task duration, and average tool calls per task.

Get per-model usage statistics: request counts, token totals (input, output, thinking, cache read, cache creation), cost, and cost per million billed tokens. Identifies the most-used model, plus any PostModelSwitch events (deliberate /model changes, automatic fallbacks, or resume) recorded this sess…

Get context window tracking: per-turn token growth, category breakdown (System/Tools/User/Assistant), fill percentage, and per-tool output contribution. Shows which tools consume the most context.

Get a breakdown of session costs by task, model, and efficiency metrics like cost per line of code. Cost figures are Preflight's own list-price estimate unless costRateMultiplier/dataResidencyPremium are configured for an org's contracted rate — see rate_multiplier_applied in the response.

Get current AI spend vs. configured budget caps (session, daily, weekly). Returns remaining budget, % used, and any threshold alerts fired this session.

Get a list of past sessions with summary metrics (efficiency, cost, tool calls, outcome).

Get a weekly summary report with per-developer breakdown, cost, efficiency, and anti-pattern counts.

Get trend data for a metric over time: weekly efficiency, cost, task success rate, or tool call counts.

Get a developer's collaboration profile: specificity, autonomy, correction rate, task complexity, and classification.

Get cost breakdown by outcome type (bug fix, feature, refactor, etc.) with waste ratio and ROI estimate.

Get personalized optimization recommendations covering cost, efficiency, prompt engineering, CLAUDE.md impact, and model selection.

Get a data-driven model recommendation ranked by historical efficiency score, cost, and task success rate across past sessions, both overall and broken down by task outcome type (bug_fix, feature, refactor, investigation, configuration, documentation, failed_attempt).

Get aggregated AI coding cost and efficiency metrics for all developers in the configured team, queried via New Relic NRQL. Requires teamId to be set in config.

Register a Slack webhook URL to receive weekly AI coding cost and efficiency summaries.

Remove the registered Slack webhook for weekly digests.

Generate the current weekly AI coding summary and POST it to the configured Slack webhook immediately.

Get thrashing/retry detection alerts: repeated failures or highly similar inputs within a sliding window. Identifies when the agent is stuck in a loop.

Get per-turn token breakdown by category (system prompt, conversation history, tool results, injected files). Shows context window fill percentage and dominance alerts. LIMITATION: system_prompt and injected_file_content are always 0 -- the model API's aggregate usage counts have no breakdown by con…

Get latency decomposition: how much time is spent in LLM API calls vs tool execution vs overhead, with p50/p95 percentiles for each component.

Get decision branch analysis: reasoning and action extraction per turn for triggered branches (recovery, retry, delegation), with outcome tagging. Includes post-mortem of failure chains and longest failure streak. LIMITATION: the reasoning field is the model's own thinking/text output only when NEW_…

Get tool selection quality score: evaluates efficiency of tool usage by detecting redundant reads, repeated failures, and unused large outputs. Score 0-1 where 1 is perfect.

Get quality proxy metrics: diff apply rate, test pass rate, backtrack count, self-correction count, and degradation detection over the session lifetime.

Get API failure tracking: per-model reliability scorecards, tokens lost, cost impact, throttle alerts, and mean time to recovery. Failures are captured via Claude Code's StopFailure hook, so totalFailures/byErrorType/bySessionPhase reflect real observed failures. LIMITATION: token loss, recovery tim…

Get compute waste summary: total tokens wasted on retried tool calls and anti-pattern activity (stuck loops, redundant reads, thrashing). Includes per-pattern breakdown and a status assessment (clean / moderate / needs_attention).

Get current session observability metrics: tool call counts, success rates, file access stats, and duration summaries.

Check server health: version, uptime, session ID, and connection timestamp. Also reports whether telemetry event sends are succeeding. Use when the MCP connection feels stale or tools are behaving unexpectedly.

Show the current server configuration (sensitive fields masked): mode, developer, account, region, storage path, dashboard URL, and config file location. Use to diagnose misconfiguration without exposing credentials.

Get an ordered list of recent tool calls with timestamps, names, durations, and success/failure status.

Cost attribution per tool type — approximate, based on turn-level token correlation. Shows which tools cost the most and average cost per call. Also breaks Skill calls down per skill in costBySkill (calls, estimated cost and tokens, total duration).

Conversation turn analysis — groups tool calls by AI response, shows parallelism and turn patterns.

Get Git workflow efficiency metrics: merge conflicts, aborted operations, force pushes, stale branch detection, and actionable suggestions to reduce Git friction.

Get the complete tool call trace for a task, including sequence, duration, and anti-pattern/efficiency analysis.

Get detected anti-patterns (thrashing, re-reading, stuck loops, blind editing, over-delegation) for the most recent task.

Get the AI coding efficiency score for the most recent task or the session-wide rolling average.

Record user quality feedback for a task. Helps correlate efficiency metrics with perceived quality.