| name | probe-before-wire |
| description | Use before baking an external config value — a model id, endpoint, ARN, bucket, region, credential, API version, image tag — into code or a deploy. Invoke the real dependency ONCE against the target account/environment and read the response, so a dead/renamed/deprecated/permission-blocked value is caught at the source instead of failing in production. The config equivalent of "verify against reality, not the doc." Triggers — "probe before wire", "smoke the dependency first", "is this model/endpoint/ARN actually live", "verify the config before deploy", "does this id still work", "check it against the real account". |
| user_invocable | true |
probe-before-wire
A config value copied from a doc, a PRD, a prior project, or your own memory is an unverified claim about an external system you don't control. Providers retire model ids, rename endpoints, deprecate API versions, rotate ARNs, and gate first-use behind a form — on their schedule, not yours. The doc that was right when it was written silently goes stale.
The discipline: before a config value enters code or a deploy, invoke the real thing once against the target account/environment and read what comes back. One live round-trip turns "this id should work" into "this id returned a 200 / a completion / the expected shape" — or surfaces the exact failure (Legacy, AccessDenied, NotFound, needs-EULA) while it's a one-line fix instead of a production incident.
This is maximize-verification's "anchor on an oracle you didn't author — verify against reality, not the doc" principle, applied to configuration and infrastructure rather than code. The real dependency IS the oracle.
When to use
Reach for it whenever you're about to hardcode or set, as a default or a deploy var, any of:
- a model / inference-profile id (LLM, embeddings, vision)
- an API endpoint, base URL, or API version string
- an ARN, bucket name, queue/topic, secret name, parameter path
- a region, account id, or cross-region profile prefix
- a container image tag / digest, a package version pin
- a credential or role you assume is granted
Especially when the value came from: a doc/PRD/README, another repo, your own training data or memory, or "the obvious current version."
The procedure
- Identify the real invocation. What single call exercises this value end-to-end against the target account/env? (
aws bedrock-runtime invoke-model, a curl to the endpoint, aws s3api head-bucket, aws sts get-caller-identity for the credential, gh api for a repo setting, a HEAD for an image.)
- Confirm the identity/profile first. Check which credential/profile is actually live (
aws sts get-caller-identity) before blaming the value — an InvalidClientTokenId on the default profile is an auth problem, not a config problem. Use the right AWS_PROFILE / context for the target account.
- Use the exact shape the code will send. Match the request body / headers / version the production client uses, so the probe proves the real path, not a simplified one. (For an LLM: the same
anthropic_version, the same Messages body. For an endpoint: the same auth + content-type.)
- Invoke once and READ the response. Not just the exit code — the body. A
200 with a wrong-shaped payload still fails downstream.
- Classify the result:
- Clean success (a completion / the expected object) → the value is live; wire it in, and cite "smoke-verified against
<account/env>" in the commit body.
- A validation/format error → good news: you reached the service; the value is fine, your request shape is off. Fix the shape, re-probe.
- Legacy / deprecated / retired → the value is dead. Find the current one (
aws bedrock list-foundation-models --query "...status=='ACTIVE'", the provider's current-models endpoint, list-inference-profiles) and re-probe the replacement before wiring.
- AccessDenied / NotFound / needs-EULA / needs-use-case-form → a permission/enablement gap. Now you know exactly what the human must grant, before a deploy fails opaquely.
- Wire the verified value. Only the value that actually returned clean goes into the default / the deploy var. If the codebase has a stale default of the same kind, fix it in the same change (a dead default is a latent failure).
Why this beats "just deploy and see"
A deploy cycle is minutes-to-hours and the failure is opaque (a cold-start log line, a 5xx, a silent fallback). A direct probe is seconds and the error message names the cause. Probing before wiring also separates the two questions that a failed deploy conflates: "is my plumbing right?" vs "is the external value live?" — you answer the second one in isolation, first.
Worked example (the canonical case)
Enabling an LLM seam, the codebase's reference model id was claude-sonnet-4-20250514 (from a months-old PRD). Instead of setting the deploy var and pushing:
aws sts get-caller-identity --profile dev-admin → confirmed the right account.aws bedrock-runtime invoke-model --model-id us.anthropic.claude-sonnet-4-20250514-v1:0 ... → Access denied. This Model is marked by provider as Legacy — the reference id was dead.aws bedrock list-foundation-models --query "...status=='ACTIVE'" + list-inference-profiles → the active 4.5-generation ids.invoke-model --model-id us.anthropic.claude-haiku-4-5-... → a clean pong completion.
Result: the dead default got fixed in code in the same change, the deploy var was set to a verified id, and a production "why is enrichment silently empty" debugging session never happened. The cost was four CLI calls.
Logs as the read-only database
When a design decision needs production data but the DB sits in a private VPC with no read-only path, the service's own logs are queryable: CloudWatch Logs Insights start-query with parse/stats over the ingest/serve log lines answers volume, churn, and shape questions — e.g. rows-per-day by parsing the per-pass counters the service already emits — without any write, tunnel, or new access grant. Prefer this over installing tunnels mid-probe (a session-manager-plugin install is a write, and the probe is supposed to be read-only). If the log line doesn't carry the counter you need, that's a finding too: the observability gap goes in the plan.
QID=$(aws logs start-query --log-group-name /ecs/<service> \
--start-time $(date -v-14d +%s) --end-time $(date +%s) \
--query-string 'fields @timestamp, @message
| filter @message like /ingest pass complete/
| parse @message "rows=* connector=*" as rows, connector
| stats sum(rows) as rows_per_day by bin(1d) as day, connector
| sort day desc' --output text --query queryId)
aws logs get-query-results --query-id "$QID"
Relationship to other skills
- maximize-verification — same "oracle you didn't author" principle; this is its config/infra projection.
- verified-ship — probe-before-wire is a pre-ship gate; the verified value then flows through verified-ship's read-gated pipeline, and "smoke-verified against
<env>" is a fact you're then allowed to put in the PR body.
- ladder-the-failure — the after to this before. If you skipped probing and a wired integration is now failing opaquely, ladder-the-failure is how you localize it to the owning layer (your wiring/IAM vs an org SCP vs an account subscription vs the provider's response format) instead of guessing.
