Call capture

Turn the calls your team already records into things a repository can hold: a raw archive, an entry per call, and — once a claim has been heard twice — an update to the knowledge layer every other agent reads. Collected by a committed script, scribed by a Claude Code harness agent, delivered as one pull request.

What it does #

• Collects. scripts/collect/calls.ts pulls every call in a three-day rolling window whose transcript the recorder has finished processing, and writes one raw file per call into cadence/log/raw/calls/. Deterministic, idempotent, no LLM anywhere near it.
• Scribes. The agent reads each pending raw capture and writes cadence/log/calls/<date>-<account>.md: what was said, the GTM intel under fixed headings, the actions as checkboxes. Capped at 12 per run, fresh-first then oldest-backfill.
• Promotes. A claim reaches context/ — the knowledge layer at the repository root — only on its second independent occurrence, citing both calls.
• Stops. One pull request, never merged. The agent has repository write access and no other write path: no email, no CRM, no merge.

How it works #

1. The cron trigger fires at 07:00 UTC, after the recorder has finished processing yesterday.
2. The agent clones the repository — the project’s own, resolved from the checkout’s git origin at deploy rather than written down. The harness’s working tree is the GTM repo itself, which is what lets its output be a diff rather than a column value.
3. It runs the collector — npx tsx scripts/call-capture/collect/calls.ts — which reads CALL_RECORDER_API_KEY from the harness environment, injected by the agent’s repository.env. The agent is told not to fetch calls itself and not to edit the script’s collection rules.
4. It scribes the pending captures, then promotes what repeats.
5. It opens one pull request whose body reports four numbers: captured, scribed fresh, scribed from backfill, pending remaining. The remainder is the drain gauge; a number that never falls means the cap is too low or a class of call is failing to parse.
6. A human merges, and the next cargo-ai cdk deploy syncs context/ into the workspace context repository, where the scorer, the researcher and every other agent read it.

Adds 3 resources plus a script bundle.

The two halves, and where they land #

This cookbook has one directory per layer it touches, and the install mirrors each into its namesake in the project:

call-capture/infra/     ->  infra/call-capture/      what is declared and deployed
call-capture/scripts/   ->  scripts/call-capture/    what the agent runs

Those are the layers cargo-ai cdk init already scaffolds — infra/ is the CDK project, scripts/ is “imperative glue for runtime surfaces the CDK cannot declare yet” — so a cookbook that needs both contributes to both under its own name rather than inventing a third place.

The collect/ subdirectory is a namespace, not decoration: call recordings are the first sensor, and the next one (Slack threads, reply metadata, product usage) lands beside it as its own entrypoint rather than growing this one. The agent’s step 1 names the collectors it runs, so adding a sensor is a new file plus a line in the system prompt.

scripts/package.json is belt and braces. In a Manifest repo the CDK project root is infra/, so nothing under scripts/ is ever imported as a resource. In a project whose CDK root is the repo root, the loader imports every .ts it finds except directories carrying a package.json — without that file, cargo-ai cdk plan would import the collector and run it against the live API on every plan.

Why the split #

The collection and the judgement are different jobs, and the failure modes for mixing them are not symmetric.

A fetch loop an agent re-derives every morning is a fetch loop that silently changes shape: a window that drifts, a filter that quietly widens, a field read differently on a day the model was less careful. Nothing downstream can tell, because the archive is what everything downstream is diffed against. So the fetch is a committed script and the agent is told not to improvise it.

The scribing is the opposite. It is judgement — what was actually agreed, whether this is the same objection as last week, whether a vendor call is being misread as pipeline — and it produces a diff across a dozen markdown files. That is what harnessSlug: "claudeCode" buys: a working tree, the git history to read before writing, and a pull request. The LLM connector and languageModel fields are unused and omitted, because the harness brings its own model.

Supporting a different recorder #

The collector is a contract and one implementation, not a fork point. recorder.ts defines Recorder — a provider slug and three methods (listReady, transcript, notes) — and holds everything that is true whoever records your calls: deduplication, account slugging, the internal-domain filter, file layout, the rolling window, --dry-run. avoma.ts is the one implementation. calls.ts is three lines of wiring.

A different recorder is a new file beside avoma.ts and a one-line import swap. The compiler is what keeps that honest: a half-written adapter does not typecheck, and the error names the field that is missing. Auth deliberately stays in the adapter — Bearer, Basic and a signed GraphQL POST are three different things — while the 429 backoff is shared through fetchJson(url, init), which takes the whole request.

There is no providers/ directory holding all three behind a switch. Shipping implementations Cargo does not run means shipping code that rots, and “supported” starts implying “tested” when it means “written once from documentation”.

Why the context is not in this folder #

defineContext is a per-workspace singleton, and the knowledge layer belongs at the repository root where humans edit it — which is exactly where cargo-ai cdk init already declares it. So this folder ships none.

Placeholders (edit before deploy) #

1. CALL_CAPTURE_INTERNAL_DOMAIN — infra/agents/call-scribe.ts: your own email domain, or every internal standup is captured as a customer call.
2. CALL_RECORDER_API_KEY — exported before deploy, never committed.
3. The recorder — scripts/collect/avoma.ts is the shipped adapter. A different recorder is one new file satisfying Recorder plus a one-line import swap in calls.ts; references/providers.md carries Gong and Fireflies against the same contract.

What it does not do #

It does not contact anyone, write to a CRM, merge its own pull request, edit or delete a raw capture or an existing log entry, or touch plan/ and infra/. It reports what the field said; it does not change the strategy or the deployed engine.