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    CSV Import Failure Triage

    1

    Diagnose failed CSV imports from a redacted sample and get ranked causes, validation checks, and a safe retry plan.

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    CSV Import Failure Triage

    CSV Import Failure Triage

    Example session with this skill installed

    Our CRM rejected this CSV with: “Row 4 has 5 columns; expected 4.”

    Expected columns
    customer_id,email,signup_date,plan

    Contract

    • UTF-8, comma-delimited, header enabled
    • signup_date must use YYYY-MM-DD
    • customer_id must be unique
    • email is required
    • plan must be basic, pro, or enterprise

    Please diagnose it without requesting the full customer dataset.

    customer_id,email,signup_date,plan
00017,user1@example.invalid,2026-09-10,basic
00018,"user2@example.invalid,2026-09-11,pro
00018,user3@example.invalid,09/12/2026,enterprise,priority
00020,,2026-09-13,basic
    • Read your context and instructions
    • Compiled the csv import failure

    Failure summary

    The sample contains two structural blockers and three contract violations. The reported five-column error is directly explained by the extra priority value. An earlier unbalanced quote may also change how the importer counts logical rows, so both structural problems should be corrected before another upload.

    Minimum evidence received

    • Exact importer error
    • Expected four-column schema
    • Encoding, delimiter, header, date, uniqueness, required-field, and enumeration rules
    • Four synthetic sample records

    Ranked cause table

    RankStatusCauseSupporting evidenceDiscriminating check
    1VERIFIEDExtra fifth fieldThe enterprise,priority record contains five comma-separated values but the schema has four columnsCount parsed fields after resolving the quote error
    2VERIFIEDUnbalanced quoteThe record beginning 00018,"user2... opens a quoted field without a closing quoteRun a quote-balance check and inspect the parser’s logical-record boundaries
    3VERIFIEDInvalid date format09/12/2026 does not match the required YYYY-MM-DD formatConfirm the intended calendar date before converting it
    4VERIFIEDDuplicate keycustomer_id value 00018 appears twice although the field must be uniqueResolve the correct identifier against the source of truth
    5VERIFIEDMissing required emailThe 00020 record has an empty email fieldObtain the correct value or follow the destination’s documented rejection policy

    Safe repair pattern

    The unbalanced quote can be structurally corrected without changing the represented value:

    00018,user2@example.invalid,2026-09-11,pro

    Do not invent a replacement customer ID, email address, or date. Determine whether priority is an accidental extra value or belongs to a newer schema. Confirm whether 09/12/2026 means 2026-09-12 or 2026-12-09 before converting it.

    Validation checklist

    • Decode as UTF-8 and check for an unexpected BOM
    • Confirm every logical record has exactly four fields
    • Confirm all quoted fields are balanced
    • Match headers exactly and preserve customer_id as text
    • Validate dates against YYYY-MM-DD
    • Check required fields and unique keys
    • Restrict plan to the documented enumeration

    Retry plan

    1. Save corrections under a new filename; do not overwrite the source.
    2. Resolve the three unknown business values using the authoritative source.
    3. Run the structural and contract checks above.
    4. Retry with a small representative subset if the CRM supports test imports.
    5. Confirm that parsing and validation complete without creating duplicate records before importing the full file.

    Unknowns

    The supplied evidence does not establish whether priority should be removed or mapped to a new field, which duplicate 00018 identifier is incorrect, what the missing email should be, or how the ambiguous date should be interpreted. These require source-of-truth confirmation, not guessing.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Identify structural CSV errors like unbalanced quotes or ragged rows.Detect schema mismatches and data type conflicts against target requirements.Generate safe, synthetic repair patterns without touching PII.Create step-by-step retry plans to prevent duplicate record creation.

    About this skill

    Stop guessing why a CSV upload failed.

    CSV Import Failure Triage turns a small, privacy-safe evidence set into a structured diagnosis. It checks common structural and contract failures including encoding and BOM issues, wrong delimiters, broken quoting, ragged rows, duplicate or missing headers, invalid dates and numbers, required-field failures, duplicate keys, and schema mismatch.

    What you provide

    • The exact import error
    • The expected columns or target schema
    • Relevant importer settings
    • A header and 5–10 representative, redacted rows

    What you receive

    • A ranked cause table with VERIFIED, LIKELY, and UNKNOWN findings
    • Evidence supporting every diagnosis
    • A minimal synthetic correction pattern
    • A pre-import validation checklist
    • A reversible retry plan
    • Clearly identified unknowns and the smallest additional evidence needed

    Privacy comes first. The skill never asks for credentials, production access, cloud-drive access, database access, or a complete private customer dataset. It does not modify your source file or fabricate successful test results.

    Designed for analysts, operations teams, developers, and SaaS users who need to understand why a CSV import failed before attempting another upload.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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    Verified clean 19 days ago

    • Passed all security checks, Safe to install

    Listed19 days ago
    Updated16 days ago

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