Open an AMI survey for the workflow you have just completed. Detects the runtime, session and measurement window automatically, and adopts any stage markers you buffered with ami_mark_stage while working. Call this FIRST, after the workflow's real work is finished, so the survey's own token spend is excluded from the measurements.

Measure the workflow run: detects which agent runtime you are in, reads that runtime's own call records (token usage, model, timings reported by the provider), attributes each call to a stage or observed execution phase, and stores the result on the run. Returns the collected inventory fields. Use these numbers verbatim. If your runtime has no adapter, this says so and you should use ami_record_calls instead.

Telemetry entry point for agents NOT running in Claude Code. Post the provider-reported usage for each API call the workflow made. Every record needs model, start_time, end_time, input_tokens, output_tokens - values read from real API responses, never estimated.

Declare the workflow stage you are entering, e.g. 'Classify Severity' or 'Draft Customer Reply'. Call it as you move through the workflow to get a declared-stage Agent Effort Profile; without markers the profile falls back to AMI-observed execution phases. No survey run is needed first: markers emitted before ami_survey_begin are buffered with the timestamp you emitted them at and attached to the run when it opens. When the last stage is done, call once more with closes=true - each marker ends the stage before it, so without a closing one the final stage runs to the end of the measurement window and absorbs everything you do afterwards.

Return the AMI output-quality grading scale. Read this before grading: agent_output_grade must be one of its codes and is validated on submit.

The workflow categories a run may declare itself into, and what each one covers. A category decides which other workflows this run is compared against, so read the list rather than inventing a label.

The scorecard for a submitted run: the AMI Maturity Index, the Performance Score, the five pillars, and structured findings. Every number and finding is computed from the run's own data - the server calls no model. If a human wants this read back as prose, write it yourself from narration_brief.findings, following the instructions there.

Write the judgement sections of a run's scorecard. The server computes every number and the three sections that follow from them; these four are readings of the work that no arithmetic produces, so they are yours to write. Call ami_get_scorecard first and use narration_brief.sections_awaiting_you - it carries the brief for each. Ground every sentence in the run's own evidence; do not invent industry context you were not given.

Return the AMI survey procedure as markdown. Call this FIRST if your harness has no skill mechanism that already gave you the procedure - it tells you the call order and, for your runtime, how telemetry is obtained. Claude Code agents already have it as a skill and do not need this.

Return the survey definition: every field from Collection_Inventory.csv, how each one is obtained, and which ones you must answer yourself.

Show the current values collected for the active run, which inventory fields are still empty, and what is blocking submission.

Submit and persist the survey. Requires a grade from the AMI grading scale, a justification, and evidence (the concrete artifacts produced). Writes JSON + Markdown + a CSV index row to disk and returns the paths.

Render the human-readable Markdown report for a run (defaults to the active run). With no run and no active run, returns the index of all submitted surveys.

List all submitted survey responses and where they are stored.