chargeback-evidence-pack-0adc4f — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited chargeback-evidence-pack-0adc4f (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use this skill to turn messy order records, processor notices, customer messages, fulfillment data, and policy snippets into a reason-coded chargeback response pack. The goal is a defensible submission plan, not legal advice or a guarantee that the issuer will reverse the dispute.
Use for:
Do not use for:
Ask only for missing inputs that materially affect the dispute decision:
If the reason code is unknown, classify the dispute by the customer's claim text and mark processor-specific rules as "verify before submit."
Identify:
Read references/dispute-evidence-rules.md before building the response if the dispute involves reason-code mapping, sensitive evidence, or the accept-versus-challenge decision. Use its platform reason-code crosswalk to translate processor labels into this skill's normalized categories, and mark any uncertain mapping as "verify before submit."
Recommend accepting or refunding when:
Recommend challenging only when the facts and evidence support the claim being invalid or incomplete. Never convert weak evidence into certainty.
For file-backed cases, run:
python3 chargeback-evidence-pack/scripts/chargeback_evidence_pack.py --case /absolute/path/case.json --evidence-dir /absolute/path/evidenceThe case JSON may include:
{
"processor": "Stripe",
"dispute_id": "dp_123",
"reason_category": "product_not_received",
"product_type": "physical",
"amount": "249.00",
"currency": "USD",
"deadline": "2026-05-15",
"order_id": "10042",
"charge_date": "2026-04-27",
"tracking_number": "1Z999",
"delivered_at": "2026-05-01",
"avs_result": "pass",
"cvv_result": "pass",
"refund_status": "not_refunded",
"policy_accepted_at": "2026-04-27T10:42:00Z"
}For pasted screenshots or partial notes, apply the same matrix manually and label row counts, file coverage, and deadline checks as incomplete.
Create a response pack with:
Prefer facts over argument. Issuers do not need long moral claims; they need proof that addresses the reason code.
Remove or avoid:
Use processor-safe labels such as "AVS passed," "3DS authenticated," "download event at timestamp," or "carrier delivered to shipping ZIP" instead of exposing raw sensitive logs.
Use this structure unless the user asks for a different format:
## Dispute Decision
[Challenge candidate / Accept or refund / Blocked until evidence is added / Deadline risk]
## Case Summary
| Field | Value |
|---|---|
| Processor | ... |
| Reason category | ... |
| Product type | ... |
| Amount | ... |
| Deadline | ... |
## Evidence Index
| Evidence | Status | Source | Why it matters | Redaction |
|---|---|---|---|---|
## Missing Evidence
| Missing item | Severity | How to get it |
|---|---|---|
## Submission Narrative
[Concise bank-facing narrative grounded only in available evidence]
## Submit Checklist
[Deadline, file names, owner review, processor-specific checks]
## Do Not Include
[Secrets, unrelated customer data, unsupported claims, or unsafe details found]Positive physical-goods example: "Use $chargeback-evidence-pack on this Shopify chargeback. Customer says product was not received, but UPS shows delivered and AVS passed." The skill should map the case to product-not-received, request or index delivery proof, order receipt, address match, customer communication, refund status, and produce a concise narrative without promising a win.
Positive SaaS example: "A Stripe customer disputed a subscription renewal as cancelled. We have terms acceptance and usage logs." The skill should focus on subscription terms, cancellation history, renewal notices if available, post-charge usage, customer messages, and refund status.
Negative example: "Write a legal threat letter to scare this customer after a chargeback." Do not use this skill for threats or collection tactics; instead explain safe dispute-response boundaries.
Boundary example: "I only know the processor says fraud and the deadline is tomorrow." The skill should produce an urgent evidence request list and a limited draft, but it must not invent authorization, delivery, identity, or policy facts.
Smoke-test the bundled fixture:
python3 chargeback-evidence-pack/scripts/chargeback_evidence_pack.py --case chargeback-evidence-pack/scripts/fixtures/case_product_not_received.json --evidence-dir chargeback-evidence-pack/scripts/fixtures/evidence --today 2026-05-14Expected result: a Markdown report that classifies the dispute as product not received for physical goods, marks delivery/order/policy evidence as present, flags customer communication as missing, notes sensitive-file redaction risks when present, and gives a challenge-candidate decision only after owner review.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.