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 skills add GoogilyBoogily/googilyboogily-claude-power-tools --skill lld-gathergit clone --depth 1 https://github.com/GoogilyBoogily/googilyboogily-claude-power-toolsWrote 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/googilyboogily/googilyboogily-claude-power-tools/lld-gather)<a href="https://agentmods.dev/skills/googilyboogily/googilyboogily-claude-power-tools/lld-gather"><img src="https://agentmods.dev/badge/skills/googilyboogily/googilyboogily-claude-power-tools/lld-gather/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/googilyboogily/googilyboogily-claude-power-tools/lld-gather"><img src="https://agentmods.dev/badge/skills/googilyboogily/googilyboogily-claude-power-tools/lld-gather.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 | $0.00053 | $0.01715 |
| Opus 5 | $0.00026 | $0.00857 |
| Sonnet 5 | $0.00011 | $0.00343 |
| Haiku 4.5 | $0.00005 | $0.00171 |
Grade A, and why
lld-gather 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 12d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLD Context Gathering — Compiler Mode
Compile all context needed to write a Low Level Design document. In the full pipeline, this skill receives a decisions file (from lld-discuss), a research file (from arch-research), and an HLD reference, then merges them with gap-fill questions to produce the final context file.
Can also run standalone — if no decisions file is provided, falls back to direct Q&A mode.
Input
$ARGUMENTS — path to a decisions file or HLD, and optionally flags.
Parse for:
- Decisions path —
docs/context/lld/<name>-decisions.md - HLD path —
--hld <path>or first arg if it looks like an HLD file path - Research path —
--research <path> - Description — if no files, treated as topic for standalone mode
Source Integrity Rules
Every factual claim in the context file must be traceable to research performed in this session.
- Cite your work. Reference specific file paths + line numbers.
- Never reference prior Claude sessions or Claude memory.
- Assumptions are labeled, not hidden.
Process
Human-in-the-loop: Never proceed past a decision point without user approval.
Mode Detection
Check if $ARGUMENTS points to a decisions file:
- If YES → Compiler Mode (Phase 1-4)
- If NO → Standalone Mode (Phase S1-S5)
Compiler Mode
Phase 1: Load Inputs
- Read the decisions file. Extract all D-XX decisions, HLD Constraints, Existing Code Patterns, Deferred Ideas, Open Questions.
- If
--hldprovided, read the HLD. Extract:- Component boundaries and responsibilities
- API contracts and data models
- Key design decisions and rationale
- Implementation phases and dependencies
- If
--researchprovided, read the RESEARCH.md. If not, check for<name>-RESEARCH.md. - Scan
docs/lld/for existing LLDs.
Phase 2: Gap-Fill Questions
Compare decisions + research + HLD against LLD context needs:
| Required Section | Source | Gap-Fill Needed? |
|---|---|---|
| Error Handling & Edge Cases | Decisions file (D-XX on error handling) | Ask for specific error codes if missing |
| State & Concurrency | Decisions file | Ask if stateful and not covered |
| Data Contracts | Decisions + HLD API contracts | Ask for exact types if missing |
| Integration Details | Decisions + HLD external systems | Ask for timeouts/retries if missing |
| Performance Constraints | Decisions | Ask for specific numbers if missing |
| Testing Strategy | Decisions (D-XX on testing) | Ask if approach unclear |
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.
- 12d ago First seen · 224 lines · 53 tokens per session scan A 88fbd1283174
lld-gather is a skill published in the GitHub repository GoogilyBoogily/googilyboogily-claude-power-tools (2 stars, last pushed 4mo ago), licensed MIT. It adds 53 tokens to every session and 1,715 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.
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