SKILLEMALL.ai

BF call-capture

Every call the team records is collected into the cadence layer each morning, scribed into a log entry, and — once a claim repeats — promoted into the context knowledge layer, as one reviewable pull request against your GTM repo. Triggers: "our call recordings never make it into the knowledge base", "turn our call transcripts into context", "keep our context updated from sales calls", "we relearn the same objection every quarter", "scribe yesterday's calls into the repo every morning", "replace the GitHub Action that summarizes our meetings". Cargo CDK, defineAgent, harnessSlug claudeCode, repository env, GitHub, Avoma, Gong, Fireflies, cadence, context. Skip when: you want one call summarized right now, which is a read against the recorder's own API and needs nothing deployed.

ClawHub Agent Skills author: Cargo v0.1.0 MIT-0 13 files body ≈ 5 500 tokens Open the sourceclawhub.ai analyzed 3 d ago

Every call the team records is collected into the cadence layer each morning, scribed into a log entry, and — once a claim repeats — promoted into the context…

As a process F 46/100 · Will not run — References files that are not bundled: scripts/collect/<recorder>.ts, scripts/call-capture/package.json

IntegrationGitHubSoftware developmentInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
69
Run on models
none yet
Process rating
F
46/100
Will not run
References files that are not bundled: scripts/collect/<recorder>.ts, scripts/call-capture/package.json
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • medium Exfiltration net-credential-use references/providers.md:62
    Credential used in a network call (verify the destination is the intended service)
    curl -s -H "Authorization: Bearer $CALL_RECORDER_API_KEY" \

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5500 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/collect/<recorder>.ts
  • warning missing-ref reference to a missing file: scripts/call-capture/package.json
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 46/100

Will not run. References files that are not bundled: scripts/collect/<recorder>.ts, scripts/call-capture/package.json
  • 0Tools and files. 2 referenced file(s) missing: scripts/collect/<recorder>.ts, scripts/call-capture/package.json
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 40Result and completion. Does not say what the result is
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 5500 tokens
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (5 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 6 example trigger phrases
  • +3Description length 788: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 33 items
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This skill does what it says: it uses a scheduled repo-writing agent to turn recorded calls into reviewable repository updates, with sensitive access clearly disclosed.
LLM: benign (high) · VirusTotal: · 3 Sept 2026