* Stop documenting the first-party enrichment provider
Its playbook, its 21 priced actions, and every recipe step that led with it
are removed. Each one now leads with the rung the pack already named as its
fallback, so nothing here is invented — the replacements were sitting in
stage-action-map.md and alternatives.md the whole time.
The substitutions:
firmographics aiArk.enrichCompany (0.01) -> companyEnrich (0.25) -> waterfall (1)
person aiArk.enrichPerson (0.1) -> waterfall.enrichContact (2)
funding enrichCrm.getFunding (1), now the catalog's only one
technographics builtwith.getDomainSummary (free) -> enrichDomain (1)
dedupe free storage query against the workspace's own models
That last line is the one worth reading twice. The match actions existed to
mint an id the other actions required; every replacement keys on the domain
or a LinkedIn URL, so a step that cost 0.5/record now costs nothing.
The event feed has no replacement and the recipes say so. fetchBusinessEvents
took a timestamp_from and nothing else in the catalog does, so funding-watch,
re-engagement and lost-deal-revival are rewritten as a diff: re-pull, compare
against the stored round date, keep what moved. Cadence becomes the only cost
dial, which is why funding-watch's default drops from daily to weekly.
Every credit budget was recomputed rather than relabelled:
build-tam 2,955 -> 2,210 (500 companies + 1,500 contacts)
prospecting P2 821 -> 107 (200 verified prospects)
icp-discovery 602 -> 204 (200 deals)
context bootstrap 3 -> 1
Catalog counts now follow the generated data file rather than the older
hand-kept figure: 136 integrations, 176 credits-based actions of 513.
Also bumps the CLI pin 1.0.66 -> 1.0.78.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019wkwbhrEoE5KW9A1CKBmcA
* Fix the three generated artifacts the removal invalidated
CI caught what the local lint could not: skills-lint.mjs is only one of five
checks, and the other four all had something to say.
llms.txt was stale — it is generated from the skill descriptions, and
cargo-gtm's dropped a provider from its roster.
The codex package build enforces override version == upstream version, so
bumping only .github/package-overrides/cargo-quickstart.SKILL.md to 1.0.3 broke
it. The guard exists to stop the override silently shipping last month's demo,
so the fix is to bump both, not to revert the override.
That build also patches literal source strings at package time, and one anchor
ran through a line this branch rewrote:
snitcher.searchSessions (0 cred) -> cargo.matchProspect
snitcher.searchSessions (0 cred) -> aiArk.reverseLookup (0.05)
The edit strips the visitor-de-anonymisation path from the packaged skill, so a
silent miss would have shipped it. Re-anchored, and every other PACKAGE_EDITS
find string verified against the tree — 1 broken, now 0.
Also drops the packaged cargo-connection description from 138 integrations to
136, matching the repo.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019wkwbhrEoE5KW9A1CKBmcA
* Say where revenue went, and that employee ratings went nowhere
Removing the provider took two data points off the map without replacing the
map entry, which is the failure mode this recipe's own feasibility gate exists
to prevent: an attribute that quietly stops being answerable reads the same as
one nobody asked for.
They are not the same case, so they get different rows.
Revenue and NAICS survive. companyEnrich.enrichByDomain (0.25) returns them in
the same call as firmographics, employees, funding and socials — so it fills
several rows at once and the row says that, because the per-account arithmetic
in step 4 gets it wrong otherwise.
Employee ratings have no successor at any price. Nothing credits-based in the
catalog returns Glassdoor-style employer reputation. The row says none, and
says to report it as a research note rather than substituting a scrape that
reads like the real thing — which is the recipe's stated position on valuable
attributes with no obtainable source, applied to itself.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019wkwbhrEoE5KW9A1CKBmcA
* Fix the data-flow breaks the provider swap left behind
Bugbot found eight, all real, and verifying them turned up five more. The
pattern in every case is the same: I replaced an action but left the code that
consumed its output reading the old response shape, so the step still runs,
still bills, and quietly returns nothing.
Response-shape breaks:
funding-watch Pattern A still filtered funding_rounds[].announced_date
while Pattern B read lastFundingDate. The 90-day select
matched nothing, so the primary path returned an empty
list after a paid pull.
re-engagement Step 5 read .results[] and .events[] from a file step 3
now writes as a bare array. Funding branch always empty.
lost-deal-revival Step 4 read .events[0] and expected a deal_id that
getFunding does not return. Step 3b now carries deal_id
through, which is the only place it exists.
Wrong-source breaks:
re-engagement The diff read last_funding_round_at off the Contacts
segment. It is a Companies column, so the stored date was
always empty and every account re-flagged every week. Now
queries the Companies model, and fans the company-level
signal back out to contacts, since step 5 unions on email.
build-tam Step 4 keyed searchLeads on .linkedinId from the
aiArk.enrichCompany output. No enrichment action returns a
Sales Navigator accountId. Now carried from the sourcing
step, with an explicit gate for rows that have none.
guide snitcher.searchSessions identifies a COMPANY; I had
chained it into aiArk.reverseLookup, which needs an email
or phone. Its own playbook says to route identified
domains through the enrich chain.
Budget break:
prospecting P2 step 5 ran FullEnrich over every lead while the budget
quoted the residue. 200 credits against 60. P1 had the
gate; P2 did not.
Pre-existing, fixed because the fixes above sit inside them:
icp-discovery [.[] | {domain}] over storage query execute output, which
is {rows: [...]}. Enriched one null domain, not 200.
jq inputs[N] `inputs` is a generator, not an array, so the union
expressions in re-engagement and lost-deal-revival errored
out. Slurped to [inputs] as $in.
Every rewritten jq expression was run against fixtures rather than eyeballed.
Also five provider mentions the sweep missed, because they wrote it as bare
`cargo` with a price rather than cargo.actionName: societeInfo, snitcher,
enrichCrm, linkedin, oceanio, apolloio, rocketreach.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019wkwbhrEoE5KW9A1CKBmcA
* Make funding-watch Pattern B stand on its own
It re-pulled two hardcoded example domains and then diffed them against
/tmp/targets.json, a Pattern A artifact. Run Pattern B alone and the slurp
fails; run both and it compares a fresh pull of one set against stored dates
for a different set, so the "new round" filter cannot fire correctly either way.
Both sides of a diff have to come from the same query. Now they do: one storage
read supplies the domains to pull *and* the stored dates to compare against, so
the sets align by construction and the pattern has no cross-dependency.
Also states what a missing stored date means — it compares against "" and always
passes, which is right on a first run and is exactly why the write-back step is
not optional. Without it every run is a first run and the watch re-flags the
whole segment forever.
Verified against fixtures: an account whose round moved is kept, one whose
stored date already matches is dropped, one with no stored date passes.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019wkwbhrEoE5KW9A1CKBmcA
* Route the questions people ask but the map never answered (#124)
Measured instead of guessed. Of the 176 credits-based actions, 148 were
reachable from a routing surface — the stage map, the phase guides,
alternatives.md, a recipe. The other 28 were reachable only from their own
provider playbook, which is findable if you already know which provider to
open. That is the wrong way round.
The worst of it: headcount had no section at all. It is the most-asked company
attribute and the first row of the custom-datapoints feasibility gate, and not
one of the four salesNavigator.find* actions appeared anywhere in the stage map.
New section carries all four, plus the only historical series
(companyEnrich.getWorkforce), plus linkedin.findCustomHeadcount for the roles
the fixed buckets don't have, plus the companyId prerequisite that quietly
turns a 0.25 action into 0.30 on a list that arrived without one.
"Who works at this domain" was not a documented question either. It is not the
same as searching a population by title, and it has two answers at very
different prices. New section, with the trap stated: looping hunter.searchDomain
to build a list is the pitfall its own playbook warns about.
Also adds rocketreach, mixrank and societeInfo to Enrich/Sourcing —
societeInfo reaches French registry data (NAF code, collective agreement,
filed accounts) that nothing else in the catalog does — and gives Hiring intent
a second index at the same price.
154/176 now. The remaining 22 stay unrouted on purpose, and the CHANGELOG says
why for each: the four LinkedIn engagement actions would undercut the
acceptable-use refusal to batch-blast them, three natives belong to other
skills, searchLeadsLegacy costs 300x its replacement, and the rest are finer
grain on an already-routed surface rather than separate questions.
One thing the build caught: adding aiArk.analyzePersonality re-introduced a
term the codex package deliberately strips, since the directory rejected
person-level inference. Kept for the channels that carry it, with matching
PACKAGE_EDITS so the package still removes it. Dropped the forager rung rather
than add machinery for a last-resort action priced 20x above its own chain.
All 67 anchors verified.
Claude-Session: https://claude.ai/code/session_019wkwbhrEoE5KW9A1CKBmcA
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
7.5 KiB
name, description, version, compatibility, homepage, metadata
| name | description | version | compatibility | homepage | metadata | |||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| cargo-quickstart | Guided first-run demo for Cargo — one persona question to 25 real leads with a cost receipt in under two minutes, ending by saving the pull as a recurring play. Triggers: "show me what Cargo can do", "give me a demo", "take me on a tour", "quickstart", "getting started with Cargo", "I just installed Cargo", "my workspace is empty", "does this actually work". Skip when: the user has a real job to run (build a list, enrich a CSV, find emails) — use cargo-gtm; when they want CLI reference or routing — use the cargo router skill. | 1.0.3 | Requires @cargo-ai/cli (npm). Sign in or create an account with `cargo-ai login --email` (emailed code, no browser), `--oauth`, or an API token | https://github.com/getcargohq/cargo-skills |
|
Cargo Quickstart — first value in two minutes
One guided demo: pull ~25 fresh leads matching a buyer persona the user picks, show the cost receipt, then save the pull as a recurring play. The point is not the list — it's that in minute 3 the user owns a running system, not a one-off result.
A new account starts with 100 free credits — no card. This demo spends about 0.5 of them. Say that out loud before the first paid call ("this costs about half a credit of your 100 free ones"): it converts the moment from a purchase decision into a look around, which is the whole job of a quickstart. Never let a new user think the demo is why they'd run out.
Bootstrap
Already signed in (cargo-ai whoami returns a workspace)? Skip to the next section.
npm install -g @cargo-ai/cli # no global install? prefix every command with `npx @cargo-ai/cli`
cargo-ai login --email you@company.com # emailed code, no browser; creates the account on first use
# alternatives: --oauth (browser) · --token <api-token> (CI)
cargo-ai whoami # confirm the active workspace before any write
Every command prints JSON to stdout; failures exit non-zero with {"errorMessage": "..."}. Anything that creates a run or a batch is async — pass --wait-until-finished or poll the matching get. When the full skill bundle is installed, ../cargo/references/prerequisites.md adds the CLI version pin, token scopes, and the admin-only surface.
The one question
Ask exactly one question before doing anything:
"Who do you sell to?" (a persona in a few words — e.g. "Heads of RevOps at mid-market SaaS")
Everything else — provider, filters, limits — you decide. Don't ask about output format, volume, or providers; defaults below.
Speed budget — HARD RULES
The demo has a two-minute budget from answer to deliverable. On the fast path:
- No discovery detours. Do not run
cargo-ai --version,cargo-ai whoami,connection connector list, or any exploratory command first. Auth problems will surface as errors on the first real call — handle them then. - One command block per step, no narration between commands.
- Paid work is capped at ~1 credit total. The demo uses the cheapest sourcing action in the catalog (
salesNavigator.searchLeads, 0.02/record → 25 records ≈ 0.5 credits). Nothing else paid runs without asking. - Never dead-end. Every step has a fallback (ladder below). If a rung fails, drop one rung silently and keep moving.
Fast path
Translate the persona into a searchLeads filter (quote the exact title phrase in keywords; a bare keyword matches loosely and pollutes the page) and run:
# 1. Execute — returns a run object; note run.uuid and run.workflowUuid.
# searchLeads returns a 25-row page minimum (limit below 25 still bills 25 × 0.02 = 0.5 credits).
cargo-ai orchestration action execute \
--action '{"kind":"connector","integrationSlug":"salesNavigator","actionSlug":"searchLeads"}' \
--data '{"keywords": "\"<persona title phrase>\"", "limit": 25}' \
--wait-until-finished > /tmp/quickstart-run.json
# 2. Fetch the output data (NOT in the execute stdout) — signed URL, then filter to THIS run
RUN_UUID=$(jq -r '.run.uuid' /tmp/quickstart-run.json)
WF_UUID=$(jq -r '.run.workflowUuid' /tmp/quickstart-run.json)
curl -s "$(cargo-ai orchestration run download-outputs \
--workflow-uuid "$WF_UUID" --output-node-slug action --format json | jq -r '.url')" \
> /tmp/quickstart-outputs.json
# 3. Show the table (the file holds ALL of the workflow's runs — filter by _uuid;
# each row's .output is the leads array directly, fields are snake_case)
jq -r --arg u "$RUN_UUID" \
'[.[] | select(._uuid==$u)][0].output[] | [.full_name, .job_title, .company_name, (.recently_hired // false)] | @tsv' \
/tmp/quickstart-outputs.json | head -25
Show the table (name · title · company · recently-hired), not the raw JSON. recently_hired: true rows are the demo's headline — lead with them ("6 of these 25 just started the job — the exact moment to reach out").
Fallback ladder (on auth/error, drop a rung — don't stop)
salesNavigator.searchLeads(0.02/record) — primary.theirStack.searchJobs(0.5) — reframe as "companies hiring your persona right now" (job postings for the persona's title). Same wow, different angle.waterfall.searchProspects(3/record) — exceeds the ~1-credit demo cap, so this rung asks first: "The two cheap sources aren't connected; I can pull 5 matches via waterfall for ~15 credits instead — run it, or connect Sales Navigator first (free)?" Run only on an explicit yes, withlimitcapped at 5.- Nothing connected at all → run the free path:
cargo-ai connection integration list | head, show what could be wired, and offer to connect one (browser auth) — the demo resumes after.
The receipt (mandatory, verbatim discipline)
The demo is itself the pilot from ../cargo-gtm/references/cost-discipline.md. Close it with a receipt:
- Credits spent + balance remaining (
cargo-ai billing subscription get— remaining =subscriptionAvailableCreditsCount − subscriptionCreditsUsedCount). For a brand-new account, frame it against the 100 free starting credits rather than as a bare number — "0.5 spent, 99.5 of your 100 free credits left" lands very differently from "99.5 credits remaining". - Hit-rate: "25 of 25 returned" (or what actually came back, and which rows look off).
Minute 3 — save it as a play
Immediately offer to make the pull recurring — this is the step that shows what Cargo is:
"Want this to run by itself? I can save this exact search as a play that runs weekly and writes new matches into a model — new
<persona>leads land without you asking."
On yes, follow ../cargo-gtm/recipes/save-as-play.md with the demo's action + filter as the workflow body and a weekly cron.
After the demo — route onward
Propose 2–3 next steps grounded in the rows just pulled, per the next-step spec in ../cargo-gtm/SKILL.md (§4): e.g. "enrich these 25 with firmographics (~0.5 cr each)", "find + verify emails for the best 10 (~1.4 cr each)", or something else entirely. From here, real GTM work belongs to cargo-gtm — read it before anything beyond the demo.