sumo-qa-finding-test-data

sumo-qa-finding-test-data is a skill for Claude Code, Codex from sumithr/sumo-qa. It costs 80 tokens per session (1,472 once invoked), scanned A, original, Apache-2.0.

A router for finding, checking, and registering test data. Test data means the accounts, records, or fixtures used to verify software behaviour.

In plain words
What is it for?
Use it to identify the data a test needs, find a known-good record, validate an existing record, or save verified data for later tests.
Why use it?
It prevents tests from relying on invented or outdated records by requiring data to be checked against the source system.

Skill for Claude CodeCodex

Part of the sumo-qa plugin — 20 skills, 2 agents, 3 hooks, 1 MCP server shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/sumithr/sumo-qa/sumo-qa-finding-test-data
Any agent
npx skills add sumithr/sumo-qa --skill sumo-qa-finding-test-data
Clone the repo
git clone --depth 1 https://github.com/sumithr/sumo-qa

Made for: Claude Code, Codex.

Or install sumo-qa, the plugin that ships this one along with the rest of its 20 skills, 2 agents, 3 hooks, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for sumo-qa-finding-test-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/sumithr/sumo-qa/sumo-qa-finding-test-data.svg)](https://agentmods.dev/skills/sumithr/sumo-qa/sumo-qa-finding-test-data)
Your own site
<a href="https://agentmods.dev/skills/sumithr/sumo-qa/sumo-qa-finding-test-data"><img src="https://agentmods.dev/badge/skills/sumithr/sumo-qa/sumo-qa-finding-test-data.svg" alt="Measured on agentmods" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,472 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00080 $0.01472
Opus 5 $0.00040 $0.00736
Sonnet 5 $0.00016 $0.00294
Haiku 4.5 $0.00008 $0.00147

Measured 4d ago against content hash 5c34d6ed7fc2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sumo-qa-finding-test-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/sumo-qa-finding-test-data/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Finding test data

Announce at start: "Finding test data — validated fresh."

Output discipline (mandatory)

Inherits the global discipline from using-sumo-qa: output discipline (never surface internal taxonomy labels — say "behaviour change in pricing", not "Classification: business_logic_change"), output economy (spend output on findings not framing; no preamble or self-narration; one question per turn; no closing pleasantries), knowledge authority hierarchy, internal scaffolding stays internal, and specialty-tool fit.

The Iron Law

STALE IS A DEFECT. NEVER INVENT ENTRIES NOT IN THE CATALOGUE.

A catalogued entry not re-validated against the source system in this turn is no better than an invented one — validation is the proof, not ceremony.

find_test_data MUST be immediately followed by validate_test_data against the returned record IN THE SAME TURN before the record is considered usable.

When to Use

User intents that trigger this skill:

  • "what test data do I need for X"
  • "find me a known-good record for X"
  • "is this record / account / fixture still valid"
  • "save this as known-good test data"
  • "I need a locked account for the failed-login test"
  • "I need a pending invoice for the due-date boundary test"

Checklist

Track these as an ordered work list (use the host's task primitive if available, otherwise a numbered inline tracker) and complete in order. Steps 1–2 are AI-only homework (route the request, gather inputs from prior conversation). The user's confirmation gate only applies to register (step 5b) — writing to the shared catalogue is a side effect that should always pause for confirmation.

  1. Pick the route (no user question — derive from intent). The four routes are internal dispatch data, NOT a label to echo at the user:
    • Explain requirements: "what data do I need" → sumo_qa_explain_test_data_requirements
    • Find: "find me a record" → sumo_qa_find_test_data
    • Validate: "is this still valid" → sumo_qa_validate_test_data
    • Register: "save this as known-good" → sumo_qa_register_known_good_test_data
  2. Gather inputs from intent + prior conversation (no user question if the conversation has them). Question, environment, domain, criteria, entry path — pull from what's already been said. Only ask if a genuinely required field is missing, and ask ONCE.
  3. For explain: call the tool. Return the requirements as text in natural English.
  4. For find: call the tool with the gathered criteria. If matches: pipe each into validate (step 5a). If no matches: say so explicitly — do NOT invent and do NOT silently broaden the criteria.
  5. For validate:
    • 5a (from find or direct): call sumo_qa_validate_test_data against the source system in this turn. A cached or memorised result is not fresh. Report state with timestamp + the validation evidence.
    • 5b (register): confirm with the user before writing to the catalogue. Show the entry, the validation evidence, and ask: "Register this as known-good?" Only write on explicit yes. Arg shape: call sumo_qa_register_known_good_test_data(entry={...}) with entry as a literal dict (id, environment, domain, scenario_tags, known_valid_for, constraints, owner, last_validated_at, confidence, source, notes). Not a YAML string. The tool docstring has a complete example.
  6. If an entry fails validation: mark it stale, surface the failure to the user, do NOT silently substitute another entry. The user decides whether to find an alternative or register a new one.

Read the full file on GitHub · 88 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 88 lines · 80 tokens per session scan A 5c34d6ed7fc2

Subscribe to this mod's changes

sumo-qa-finding-test-data is a skill published in the GitHub repository sumithr/sumo-qa (6 stars, last pushed today), licensed Apache-2.0. It adds 80 tokens to every session and 1,472 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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