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 PowerLaw-Technology/ferc-elibrary-mcp --skill ferc-elibrarygit clone --depth 1 https://github.com/PowerLaw-Technology/ferc-elibrary-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/powerlaw-technology/ferc-elibrary-mcp/ferc-elibrary)<a href="https://agentmods.dev/skills/powerlaw-technology/ferc-elibrary-mcp/ferc-elibrary"><img src="https://agentmods.dev/badge/skills/powerlaw-technology/ferc-elibrary-mcp/ferc-elibrary/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/powerlaw-technology/ferc-elibrary-mcp/ferc-elibrary"><img src="https://agentmods.dev/badge/skills/powerlaw-technology/ferc-elibrary-mcp/ferc-elibrary.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 | $0.00055 | $0.00646 |
| Opus 5 | $0.00028 | $0.00323 |
| Sonnet 5 | $0.00011 | $0.00129 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
ferc-elibrary 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 10d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FERC eLibrary MCP workflow
Principles
- Never request full document text. Large orders and tariffs can exceed a million characters.
- Cache before re-fetching. Check
cachedflags on search and docket results; usesync_docketfor incremental updates. - Locate, then read. Use
get_document_outlineandsearch_within_documentbeforeread_document.
Standard workflow
1. Discover
search_filingsfor keywords, document types, or partiesget_docketfor a full proceeding sheet- Note
cached: true/falseon each accession
2. Populate the store
sync_docketfor everything new on a docket (preferred for bulk)download_filefor a single accession or attachmentcache_statusto confirm what is already stored
3. Read substance (bounded)
For each file you need to analyze:
get_document_outline(accession, filename)— bookmarks or heuristic sectionssearch_within_document(accession, filename, query)— jump to relevant passagesread_document(accession, filename, pages=[...])orchar_start/char_end— read only what you need- If
truncated: true, continue withnext_char_startor the next page range
4. Summarize large filings
- Summarize section by section, not in one pass
- Each section: outline → search → bounded read → short summary
- Merge section summaries at the end
Anti-patterns
- Do not use
get_filing_texton 100+ page filings (deprecated; bounded and may truncate) - Do not call
read_documentwithoutpagesorchar_rangeon unknown-size documents - Do not re-download accessions already marked
cached: true
Configuration (firm shared cache)
Point FERC_STORE_ROOT at a folder the whole team can access:
- Local: shared network drive or SharePoint-synced directory (
FERC_STORE_BACKEND=local) - AWS:
FERC_STORE_BACKEND=s3andFERC_STORE_ROOT=s3://bucket/prefix(Phase 2)
Tool quick reference
| Goal | Tool |
|---|---|
| Find filings | search_filings, get_docket |
| Fill cache | sync_docket, download_file |
| Inspect cache | cache_status |
| Table of contents | get_document_outline |
| Find a phrase | search_within_document |
| Read a section | read_document with bounds |
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.
- 10d ago First seen · 70 lines · 55 tokens per session scan A d696604407a1
ferc-elibrary is a skill published in the GitHub repository PowerLaw-Technology/ferc-elibrary-mcp (0 stars, last pushed 14d ago), licensed MIT. It adds 55 tokens to every session and 646 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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