Analyzes DWARF debug information in compiled binaries. Use when inspecting .debug_* sections, DIE trees, or DW_TAG_/DW_AT_ entries with dwarfdump/llvm-dwarfdump or readelf, verifying debug info with llvm-dwarfdump --verify, answering DWARF standard questions, or writing code that parses DWARF (libdwarf, pyelftools, gimli).
npx skills add https://github.com/trailofbits/skills --skill dwarf-expert
Expertise for DWARF debug info: parsing and searching it, verifying its
integrity, answering questions about the standard, and writing code that
consumes it. Out of scope: runtime debugging (use gdb/lldb), reverse
engineering beyond the DWARF sections (use Ghidra/IDA), and compiler-specific
DWARF generation bugs.
When precision matters, look standard details up instead of answering from memory:
e.g. "DWARF5 DW_TAG_subprogram attributes site:dwarfstd.org".
llvm/lib/DebugInfo/DWARF/ is a reliable reference implementation:DWARFDie.cpp (DIE and attribute access), DWARFUnit.cpp (compilation units),
DWARFDebugLine.cpp (line tables), DWARFVerifier.cpp (validation).
Prefer dwarfdump over readelf for DWARF-specific work. Two implementations
exist — libdwarf's dwarfdump and LLVM's llvm-dwarfdump — with different
options, and a bare dwarfdump command may be either: check dwarfdump --version
first. The options below are LLVM's.
On macOS, linked Mach-O executables do not carry DWARF: it stays in the .o
files until dsymutil collects it into a .dSYM bundle. Point dwarfdump at
the dSYM (or the object files), not the executable. pyelftools is ELF-only —
for Mach-O scripted work, stay with the LLVM tools.
--all: dump every DWARF section; --debug-info, --debug-line, etc. dump one--show-children [--recurse-depth=<n>]: include child DIEs when printingselected entries — parameters, locals, and struct members are children of
function and type DIEs
--show-parents [--parent-recurse-depth=<n>]: include parent DIEs--show-form: print attribute form types, for when encoding details matter--find=<name>: exact-name lookup via the accelerator tables — fast but notexhaustive; fall back to --name when it misses
--name=<pattern> [--ignore-case] [--regex]: exhaustive DIE-name search--lookup=<address>: find the DIE covering an address--verbose: print low-level encoding detailEscalate through these strategies as the query grows more complex:
--find, then --name; --lookup for addresses.float *): dump andfilter. grep -B pulls in the header line carrying each DIE's offset:
llvm-dwarfdump file | grep -B 5 "float \*" | grep DW_TAG_formal_parameter,
then print each DIE at its offset with --debug-info=<offset> --show-children
(--lookup takes a program address, not a DIE offset).
write a Python script using pyelftools instead.
llvm-dwarfdump --verify <binary>: structural checks (unit chains, DIErelationships, address ranges). --error-display=<quiet|summary|details|full>
controls detail; --verify-json=<path> writes a machine-readable error
summary; --quiet for exit-code-only checks.
llvm-dwarfdump --statistics <binary>: debug-info quality metrics as JSON —compare across compiler versions or optimization levels to catch regressions.
Verify after producing DWARF (compilers, binary rewriters), when a debugger
misbehaves on a binary, and when developing DWARF tooling against known-good
files.
When a current-generation compiler emitted an old DWARF version, the build
explicitly passed -gdwarf-N — modern gcc and clang default to v4/v5, so check
the build system rather than assuming a toolchain default. GCC embeds its flags
in DW_AT_producer, so the pin is often readable right there; clang's producer
string carries no flags. Old versions remain common in the wild and read the
same way apart from surface forms: in v2 output, member offsets appear as
location expressions (DW_OP_plus_uconst) and linkage names as
DW_AT_MIPS_linkage_name.
For general ELF structure, or when dwarfdump is unavailable:
--debug-dump=<section>: dump a DWARF section (info, line, ...)--dwarf-depth=<n> / --dwarf-start=<n>: limit DIE depth / start offsetPrefer an existing library over parsing by hand:
| Library | Language | Notes |
|---------|----------|-------|
| libdwarf | C/C++ | github.com/davea42/libdwarf-code — low-level; used to implement dwarfdump |
| pyelftools | Python | github.com/eliben/pyelftools — also parses ELF in general |
| gimli | Rust | github.com/gimli-rs/gimli — pair with object to load container files |
| debug/dwarf | Go | standard library |
| LibObjectFile | .NET | github.com/xoofx/LibObjectFile — also handles ELF/PE object files |
Default to Python with pyelftools for one-off scripts unless the task dictates
otherwise.
DWARF-specific pitfalls to handle — and to check for when reviewing DWARF code:
DW_AT_name, DW_AT_type, ranges, etc.DW_AT_abstract_origin (inlined instances) or DW_AT_specification
(out-of-line definitions) — resolve the chain before concluding data is absent.
DW_TAG_const_type,DW_TAG_pointer_type, ...) wrap the underlying type; walk DW_AT_type links to
reach the base type.
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing. Uses GPT-5.2 by default for state-of-the-art software engineering.
Implement memory-safe programming with RAII, ownership, smart pointers, and resource management across Rust, C++, and C. Use when writing safe systems code, managing resources, or preventing memory bugs.
Python/HTSlib workflows for genomic files. Use when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
> Create, build, deploy, and localize declarative agents for M365 Copilot and Teams. USE THIS SKILL for ANY task involving a declarative agent — including localization, scaffolding, editing manifests, adding capabilities, and deploying. Localization requires tokenized manifests and language files that only this skill knows how to produce. "scaffold an agent", "new agent project", "add a capability", "add a plugin", "configure my agent", "deploy my agent", "fix my agent manifest", "edit my agent", "localize my agent", "add localization", "translate my agent", "multi-language agent", "add an API plugin", "add an MCP plugin", "add OAuth to my plugin", "review instructions", "improve instructions", "fix my instructions"
Documentation generation workflow covering API docs, architecture docs, README files, code comments, and technical writing.
Take trailofbits/dwarf-expert from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.