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 commands/marcosd4h/deepextractruntime/comgit clone --depth 1 https://github.com/marcosd4h/DeepExtractRuntimeWhat 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 | $0.00000 | $0.01174 |
| Opus 5 | $0.00000 | $0.00587 |
| Sonnet 5 | $0.00000 | $0.00235 |
| Haiku 4.5 | $0.00000 | $0.00117 |
Grade A, and why
com 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- winrt — 86% identical, 68 lines differ
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
COM Analysis
Overview
Analyze COM server interfaces in Windows binaries using ground-truth extraction data. Enumerates COM servers by module or CLSID, maps the privilege-boundary attack surface, audits security properties (permissions, elevation, marshalling, DCOM), classifies entry points, and identifies privilege escalation and UAC bypass targets.
The text after /com is the module name or CLSID and optional subcommand (e.g., /com wuapi.dll, /com surface, /com privesc).
Subcommands
| Subcommand | Usage | Purpose |
|---|---|---|
| (default) | /com <module_or_clsid> |
Enumerate COM servers, interfaces, methods |
workspace |
/com workspace |
Discover which workspace modules implement COM servers |
surface |
/com surface [module] |
Risk-ranked COM attack surface (module or system-wide) |
methods |
/com methods <module_or_clsid> |
List methods with optional pseudo-IDL |
classify |
/com classify <module> |
Semantic classification of COM entry points |
audit |
/com audit <module_or_clsid> |
COM-specific security audit |
privesc |
/com privesc [--top N] |
Find privilege escalation targets |
IMPORTANT: Execution Model
Execute immediately. Do NOT ask for confirmation before running scripts. Read the com-interface-analysis SKILL.md to understand available scripts and their options, then run the appropriate script(s) for the subcommand.
Execution Context
- Working directory: Workspace root (scripts handle their own path setup)
- Output: Scripts support
--jsonfor machine-readable output - Data: Read-only access to COM extraction data via
helpers.com_index
Steps
Step 0: Preflight Validation
Parse the user's input to determine the subcommand and target. If a module name or CLSID is given, verify it exists in the COM index by running:
python .claude/skills/com-interface-analysis/scripts/resolve_com_server.py <module_or_clsid> --json
If no servers are found, report this and suggest checking module name spelling or using surface --system-wide to see all available modules.
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.
- 2d ago First seen · 119 lines · 0 tokens per session scan A fa215a7f5280
com is a command published in the GitHub repository marcosd4h/DeepExtractRuntime (20 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,174 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.