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.
npx agentmods add skills/mort2000/gdb-lite-mcp/gdb-debuggingnpx skills add Mort2000/gdb-lite-mcp --skill gdb-debugginggit clone --depth 1 https://github.com/Mort2000/gdb-lite-mcpWrote 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/mort2000/gdb-lite-mcp/gdb-debugging)<a href="https://agentmods.dev/skills/mort2000/gdb-lite-mcp/gdb-debugging"><img src="https://agentmods.dev/badge/skills/mort2000/gdb-lite-mcp/gdb-debugging.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.00975 |
| Opus 5 | $0.00034 | $0.00487 |
| Sonnet 5 | $0.00014 | $0.00195 |
| Haiku 4.5 | $0.00007 | $0.00097 |
Grade A, and why
gdb-debugging 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.
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDB Debugging
Use GDB as the debugging engine. Keep the MCP API thin: spawn a session, send native GDB command batches, read incremental output, and close the session.
Workflow
- Read enough source to state the symptom, expected invariant, and likely boundary where the invariant first matters.
- Spawn GDB. GDB Lite applies low-noise startup defaults automatically; use
gdb_argsonly for target-specific setup. - Prefer one discriminating probe over many tiny probes.
- For repeated observations, use GDB-native automation such as breakpoint command lists, conditional breakpoints, watchpoints, or short GDB Python blocks.
- When a temporary Python script would compute expected values, replay reference logic, or compare structured runtime state, consider sourcing it as GDB Python so the calculation and inferior inspection happen in one debugger pass.
- Keep a compact hypothesis/evidence table mentally or in notes. Stop probing when the evidence identifies the earliest wrong state transition, or when a complete trace proves the expected value or fixture is inconsistent with runtime inputs.
- Close the GDB session before finishing.
Start Modes
- Use
prog_pathfor normal local execution. - Use
core_pathwithprog_pathwhen the artifact is a core file; inspectbt fullbefore rerunning. - Use
attach_pidfor an already-running local process; collect thread backtraces before changing state. - Use
remote_targetfortarget remote; pass native setup ingdb_argswhen sysroot, solib paths, or connection timeouts matter.
Interaction Economy
- Batch related commands in one
gdb_execcall. - Avoid human-style repeated
next/printcalls unless narrowing one transition. - Print labels with values when collecting traces.
- For non-hang loop traces, prefer passive before/after breakpoints over repeated stepping.
- Limit output. If a trace is large, rerun with a conditional breakpoint or narrower range.
- For hang or infinite-loop cases, do not use auto-continuing breakpoint command lists; use plain breakpoints, bounded manual
continue/next, or stop-on-condition probes instead. - Treat
timed_out && needs_interruptas "do not stack more commands." Usegdb_interrupt, then collectbt,thread apply all bt, and locals. - Treat
at_prompt=falseandcommand_pending=trueas a session-control issue before it is a debugging hypothesis. - For MCP
gdb_spawn, use a stablework_dirsuch as the target project root and aprog_pathrelative to that directory, or pass an absoluteprog_path. Avoid mixing a binary directorywork_dirwith paths already relative to another directory.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 58 lines · 69 tokens per session scan A 3dd3113e9b91
gdb-debugging is a skill published in the GitHub repository Mort2000/gdb-lite-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 69 tokens to every session and 975 once invoked, about $0.0003 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.
Other skills, from other repositories
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chat-perf
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Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
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