fix-bug

A workflow for investigating and fixing a GitHub issue in the DBHub codebase. It covers fetching the issue, reproducing the problem, implementing a fix, verifying it, and preparing a pull request.

In plain words
What is it for?
Use it when given a DBHub issue URL or number and asked to investigate and implement the corresponding bug fix.
Why use it?
It turns an issue report into a repeatable development process with attention to expected behavior, affected code, and verification.

Skill for Claude CodeCodex

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/bytebase/dbhub/fix-bug
Any agent
npx skills add bytebase/dbhub --skill fix-bug
Clone the repo
git clone --depth 1 https://github.com/bytebase/dbhub

Made for: Claude Code, Codex.

Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,461 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 $0.00034 $0.01461
Opus 5 $0.00017 $0.00731
Sonnet 5 $0.00007 $0.00292
Haiku 4.5 $0.00003 $0.00146

Measured yesterday against content hash 4386ea2e874f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fix-bug 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 yesterday.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • fix-bug — 100% identical, 0 lines differ
.claude/skills/fix-bug/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fix Bug from GitHub Issue

Systematic workflow for turning a GitHub issue into a working fix in the DBHub codebase.

Workflow

  1. Fetch → 2. Analyze → 3. Locate → 4. Reproduce → 5. Plan → 6. Implement → 7. Verify → 8. PR

Step 1: Fetch Issue

# From URL: https://github.com/owner/repo/issues/123
gh issue view 123 --json title,body,labels,comments,state

# From another repo
gh issue view 123 --repo owner/repo --json title,body,labels,comments,state
Input How to fetch
https://github.com/owner/repo/issues/42 gh issue view 42 --repo owner/repo
#42 or 42 gh issue view 42 (current repo)
owner/repo#42 gh issue view 42 --repo owner/repo

Step 2: Analyze Issue

Extract from the issue:

  • What's broken: Expected vs actual behavior
  • Reproduction steps: How to trigger the bug
  • Environment: Database type, connection method (DSN, SSH tunnel, TOML config), transport (stdio/HTTP)
  • Labels/comments: May reveal affected area or prior investigation
  • Linked PRs/issues: Check for related context

Step 3: Locate Relevant Code

Use the issue details to identify which part of the codebase is affected. DBHub has a clear modular structure — most bugs fall into one of these areas:

Bug Category Where to Look Key Files
Connection failures Connector implementations src/connectors/{db-type}/index.ts, src/connectors/manager.ts
SQL execution errors Tool handlers src/tools/execute-sql.ts, src/utils/allowed-keywords.ts
Schema/table listing Search tool src/tools/search-objects.ts
DSN parsing issues Parser logic src/connectors/{db-type}/index.ts (DSNParser), src/utils/dsn-obfuscate.ts, src/utils/safe-url.ts
SSH tunnel problems Tunnel utilities src/utils/ssh-tunnel.ts, src/utils/ssh-config-parser.ts
TOML config issues Config loading src/config/toml-loader.ts, src/types/config.ts
Multi-database routing Manager & tools src/connectors/manager.ts, src/utils/tool-handler-helpers.ts
Custom tool issues Custom handler src/tools/custom-tool-handler.ts, src/tools/registry.ts
HTTP transport Server setup src/server.ts
Read-only violations SQL validation src/utils/allowed-keywords.ts, src/utils/sql-parser.ts
Row limiting SQL rewriting src/utils/sql-row-limiter.ts
API endpoint issues API handlers src/api/sources.ts, src/api/requests.ts
AWS IAM auth Token signing src/utils/aws-rds-signer.ts

Read the full file on GitHub · 149 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. yesterday First seen · 149 lines · 34 tokens per session scan A 4386ea2e874f

Subscribe to this mod's changes

fix-bug is a skill published in the GitHub repository bytebase/dbhub (3,431 stars, last pushed 11d ago), licensed MIT. It adds 34 tokens to every session and 1,461 once invoked, about $0.0002 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 2026-08-30.

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