Borrowing it
Nothing to install: this file belongs to mehdic/bazinga. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mehdic/bazinga/main/.claude/skills/bazinga-db-workflow/SKILL.mdgit clone --depth 1 https://github.com/mehdic/bazingaWrote 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.
[](https://agentmods.dev/skills/mehdic/bazinga/bazinga-db-workflow)<a href="https://agentmods.dev/skills/mehdic/bazinga/bazinga-db-workflow"><img src="https://agentmods.dev/badge/skills/mehdic/bazinga/bazinga-db-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mehdic/bazinga/bazinga-db-workflow"><img src="https://agentmods.dev/badge/skills/mehdic/bazinga/bazinga-db-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.01390 |
| Opus 5.5 | $0.00010 | $0.00556 |
| Sonnet 5.5 | $0.00005 | $0.00278 |
| Haiku 4.5 | $0.00003 | $0.00139 |
Grade A, and why
bazinga-db-workflow 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BAZINGA-DB Workflow Skill
You are the bazinga-db-workflow skill. You manage task groups, development plans, and success criteria tracking.
When to Invoke This Skill
Invoke when:
- Creating or updating task groups
- Saving or retrieving development plans
- Managing success criteria
- Tracking plan progress
Do NOT invoke when:
- Managing sessions or state → Use
bazinga-db-core - Logging interactions or reasoning → Use
bazinga-db-agents - Managing context packages → Use
bazinga-db-context
Script Location
Path: .claude/skills/bazinga-db/scripts/bazinga_db.py
All commands use this script with --quiet flag:
python3 .claude/skills/bazinga-db/scripts/bazinga_db.py --quiet <command> [args...]
Commands
create-task-group
python3 .claude/skills/bazinga-db/scripts/bazinga_db.py --quiet create-task-group \
"<group_id>" "<session_id>" "<description>" \
[--specializations '<json_array>'] [--item_count N] [--initial_tier "<tier>"] \
[--component-path "<path>"] [--complexity N] [--security_sensitive 0|1]
Parameters:
group_id: Short identifier (e.g.,AUTH,CALC)session_id: Parent session IDdescription: Human-readable description--specializations: JSON array of specialization paths--initial_tier:"Developer"or"Senior Software Engineer"--complexity: 1-10 scale
Returns: Created task group object.
update-task-group
CRITICAL: Argument order is <group_id> <session_id> (NOT session first)
python3 .claude/skills/bazinga-db/scripts/bazinga_db.py --quiet update-task-group \
"<group_id>" "<session_id>" [--status "<status>"] [--assigned_to "<agent_id>"] \
[--specializations '<json_array>'] [--item_count N] [--initial_tier "<tier>"] \
[--component-path "<path>"] [--qa_attempts N] [--tl_review_attempts N] \
[--security_sensitive 0|1] [--complexity N] \
[--review_iteration N] [--no_progress_count N] [--blocking_issues_count N]
Valid status values: pending, in_progress, completed, failed, approved_pending_merge, merging
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.
- 2mo ago First seen · 174 lines · 25 tokens per session scan A 3d8e6e7856f9
bazinga-db-workflow is a skill published in the GitHub repository mehdic/bazinga (22 stars, last pushed 9mo ago), licensed MIT. It adds 25 tokens to every session and 1,390 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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