Spec Product Pulse

Product Pulse

spec-product-pulse queries the product's data sources for a given time window and produces a compact, single-page report covering usage, performance, errors, and followups. The report is saved to docs/pulse-reports/ and the key points are surfaced in chat.

The skill does not mutate the product, the database, or any external system. Its only writes are pulse settings appended to .spec-first/config.local.yaml (the unified spec-first local config, gitignored, machine-local) and the report file (docs/pulse-reports/...). MCP and other data-source tools are invoked read-only; if a tool offers write modes, do not use them.

Interaction Method

Default to the platform's blocking question tool: AskUserQuestion in Claude Code (call ToolSearch with select:AskUserQuestion first if its schema isn't loaded), request_user_input in Codex. Fall back to numbered options in chat only when no blocking tool exists in the harness or the call errors (e.g., Codex edit modes) — not because a schema load is required. Never silently skip the question.

Ask one question at a time. Reserve multi-select for first-run configuration only.

Lookback Window

Interpret the user's current request as a time window when one is provided. Common forms:

• 24h, 48h, 72h - trailing hours
• 7d, 30d - trailing days
• 1h - short-window (useful during launches)

If the argument is empty, default to pulse_lookback_default from config (resolved in Phase 0); if that is also unset, fall through to the hard default of 24h. If the argument is unparseable, ask the user to clarify.

Apply a 15-minute trailing buffer to the window's upper bound. Many analytics and tracing tools have ingestion lag; querying right up to now under-reports the most recent events. For a 24h window, query [now - 24h - 15m, now - 15m].

Core Principles

1. Read it like a founder. No hardcoded thresholds. Do not label things "bad" or "good" by default - present the numbers and let the reader judge.
2. Single page. Target 30-40 lines of terminal output. If the report is getting long, cut.
3. No PII in saved reports. Do not include user emails, account IDs, or message content in the report written to disk.
4. Parallel where safe, serial where it matters. Analytics and tracing queries run in parallel. Database queries run serially to avoid load.
5. Memory through saved reports. Every run writes to docs/pulse-reports/ so past pulses are browseable as a timeline.
6. Read-only database access only. If a database is used as a data source, the connection must be read-only. The interview refuses to accept read-write credentials. Database access is optional - many products complete the pulse with analytics and tracing alone.
7. Strategy-seeded when available. If STRATEGY.md exists, the interview reads it before asking questions and carries forward the product name and key metrics as seeds. The goal of data-source setup is to wire up whatever connections are needed to actually measure those metrics.

Execution Flow

Phase 0: Route by Config State

Read config. Resolve <repo-root> at runtime by running git rev-parse --show-toplevel with the shell tool. Then read <repo-root>/.spec-first/config.local.yaml with the native file-read tool. If the root cannot be resolved or the file does not exist, treat this as a first run. Otherwise extract the pulse_* keys listed below. Reports remain owned by the fixed docs/pulse-reports/ contract; this Skill does not introduce a global configurable artifact root.

Config keys:

• pulse_product_name -- string, used in report titles. Required for routing: if unset, skill is unconfigured.
• pulse_lookback_default -- one of 1h, 24h, 7d, 30d (default: 24h)
• pulse_primary_event -- string, the engagement event name
• pulse_value_event -- string, the value-realization event name
• pulse_completion_events -- comma-separated string of 0-3 event names
• pulse_quality_scoring -- true or default false (AI products only)
• pulse_quality_dimension -- string scored 1-5 when pulse_quality_scoring is true; ignored otherwise
• pulse_analytics_source -- string identifying analytics provider (e.g., posthog, mixpanel, custom)
• pulse_tracing_source -- string identifying tracing provider (e.g., sentry, datadog, custom)
• pulse_payments_source -- string identifying payments provider (e.g., stripe, custom); omit if not used
• pulse_db_enabled -- true or default false; when true, read-only DB access is part of the pulse
• pulse_metric_sources -- comma-separated metric=source pairs giving per-strategy-metric source overrides (e.g., retention_d7=posthog,nps=delighted). Strategy metrics not listed fall back to pulse_analytics_source and are rendered with a (default source) marker so the implicit routing is visible.
• pulse_pending_metrics -- comma-separated string of strategy-doc metric names awaiting instrumentation; rendered as no data in each pulse report until instrumentation lands
• pulse_excluded_metrics -- comma-separated string of strategy-doc metric names intentionally excluded from the pulse; the metric stays in STRATEGY.md but is not surfaced in pulse reports
• pulse_schedule -- daily, weekly, manual, or ask-again-after-3-runs; include time/day if applicable

Routing:

• pulse_product_name is unset (or config file missing) -> First run. Go to Phase 1 (interview), then Phase 2.
• pulse_product_name is set -> Skip to Phase 2.

If the argument was setup, reconfigure, or edit config, go to Phase 1 regardless of config state.

Phase 1: First-Run Interview

1.0 Seed from strategy (if available)

Before asking any questions, read STRATEGY.md using the native file-read tool. If the file exists, extract:

• The product name from the name key in the YAML frontmatter, falling back to the H1 title (stripping the trailing Strategy suffix, e.g., # Spiral Strategy -> Spiral) if frontmatter is missing
• The list of key metrics from the ## Key metrics section, one per line

Open the interview by surfacing what was extracted: announce that a strategy doc was found, show the seeded product name and the list of key metrics that will be carried into event/data setup, and invite the user to correct any of it before continuing.

If STRATEGY.md does not exist, note that explicitly in chat: no strategy doc on file, running setup from scratch, and mention that spec-strategy can seed pulse later if run first.

1.1 Interview

Read references/interview.md. This load is non-optional - the pushback rules, anti-pattern examples, and metric-to-source mapping logic live there.

Run the interview in this order:

1. Product name (confirm or edit the seeded value)
2. Primary engagement event
3. Value-realization event
4. Completions or conversions (0-3)
5. Quality scoring (opt-in, AI products only)
6. Data sources - wire up connections for each agreed metric and event. Nudge toward MCP. Reject read-write database access. DB entirely optional.
7. System performance - a short recommended setup for top errors and latency. Users rarely have strong opinions here; present defaults and accept.
8. Default lookback window

Apply the pushback rules in references/interview.md for each section. Treat every metric, event, and signal the user proposes against the SMART bar (specific, measurable, actionable, relevant, timely) spelled out in references/interview.md under "Overall Rules" - push back on anything vague, vanity, or unactionable.

If the user offers read-write database access, refuse and offer the alternatives documented in references/interview.md section 6.

Write the captured config to <repo-root>/.spec-first/config.local.yaml as flat pulse_* keys, using the schema in references/interview.md under "Config file shape". Resolve the repo root with git rev-parse --show-toplevel. To write: (1) if the file or directory does not exist, create .spec-first/ and write the YAML file; (2) if the file exists, merge new keys into the existing YAML, preserving any non-pulse keys (e.g., work_delegate_*, plan_*) untouched. If .spec-first/config.local.yaml is not already covered by the repo's .gitignore, offer to add the entry before writing. Show the resulting pulse block to the user in chat and offer one round of edits.

After the config is written, run the scheduling recommendation from references/interview.md section 9: offer to set up a recurring run so the user gets the pulse on a cadence instead of having to remember to run it. Accept yes/no/later. If yes, hand off to whichever scheduling primitive the current harness exposes; otherwise note that scheduling is platform-specific (cron, GitHub Actions, the host's own automation) and emit a brief hint covering what would need to run. Do not schedule inline. Then proceed to Phase 2.

Phase 2: Run the Pulse

If Phase 1 ran (first run, or setup/reconfigure argument), re-read .spec-first/config.local.yaml from the repo root using the native file-read tool to pick up any edits accepted during the Phase 1 review step. Otherwise, use the pulse_* values already extracted in Phase 0. Apply hard defaults for any unset settings (see Phase 0 "Config keys").

2.1 Dispatch Queries

Run these in parallel (different tools, no shared load):

• Product analytics query (primary event count, value-realization count, completions, conversion ratios) over the window
• Application tracing query (error counts by category, latency distribution, top error signatures) over the window
• Payments query, if configured (new customers, churn, revenue delta) over the window

Run these serially, after the parallel batch:

• Read-only database queries. One at a time. Tight, scoped queries only. Never full-table scans on large tables. If a DB query would be expensive, skip it and note "DB query skipped (estimated cost too high)".

2.2 Optional: Sample Quality Scoring

If pulse_quality_scoring is true (AI products only), sample up to 10 sessions or conversations from the window and score each 1-5 on the dimension recorded in pulse_quality_dimension.

Scoring discipline: Default to 4 or 5 when the session looks normal. Reserve 1-3 for sessions with a clear failure mode (product gave wrong answer, user got stuck, error surfaced). If every session is scoring 3, the bar is too strict; if every session is scoring 5, the bar is too loose.

No PII in the score summary. Capture a count distribution (e.g., "8x 5, 1x 4, 1x 2") and a short anonymized note on any session scored below 4. Do not include message content or user identifiers in the saved report.

2.3 Assemble the Report

Read references/report-template.md. Fill in the template using the query results. Four sections, in order:

1. Headlines - 2-3 lines summarizing the window
2. Usage - primary engagement, value realization, completions, quality sample
3. System performance - latency (p50/p95/p99) and top 5 errors by count with one-line explanation each
4. Followups - 1-5 things worth investigating

Keep the total to 30-40 lines. If a section is thin, leave it thin; do not pad.

2.4 Write the Report

Save to docs/pulse-reports/YYYY-MM-DD_HH-MM.md using the local time of the run. Create docs/pulse-reports/ if it does not exist.

Surface the Headlines and top Followup in chat. Provide the full file path so the user can open the saved report.

Phase 3: Routine Hook

First-run setup already offered scheduling (see Phase 1.1 end). Phase 3 is a lighter re-surface for ad-hoc runs:

• If the argument was a known schedule keyword (daily, hourly, weekly), note that this run is ad-hoc and suggest scheduling via the harness's available primitive, or a platform-native option when no scheduling primitive is available.
• If no schedule is on file and this is the third or later pulse run the user has done, mention once that scheduling is available. Don't nag on every run.

Never schedule automatically. Any scheduling handoff requires explicit confirmation.

What This Skill Does Not Do

• Does not report "what shipped." Shipped work lives in the issue tracker and commit history, not here. Pulse is strictly about user experience and system performance.
• Does not set thresholds or alert the user. The reader interprets.
• Does not persist PII in saved reports.
• Does not mutate the database or any external system. All queries are read-only.
• Does not replace tracing dashboards or analytics tools. It consolidates a single-page read; deep investigation still uses the native tools.

Learn More

The "read like a founder" posture and the single-page constraint are deliberate. Dashboards with 40 metrics produce attention sprawl; one page with the right four sections forces the reader to notice what matters. The saved-reports folder is designed to be a team's working memory, not a data warehouse - past pulses are grepable, diffable, and disposable.