ferc-elibrary-mcp
FERC eLibrary MCP
Ein Model Context Protocol-Server und eine asynchrone Python-Bibliothek zum Durchsuchen der öffentlichen FERC eLibrary, zum Prüfen von Docket-Listen und zum Herunterladen öffentlicher Einreichungen. Funktioniert mit jedem MCP-Client (Claude Desktop, Cursor, Claude Code und anderen).
Haftungsausschluss
FERC veröffentlicht keine offizielle eLibrary-Entwickler-API. Dieses Projekt spricht mit demselben undokumentierten JSON-Backend, das auch die öffentliche Website verwendet (https://elibrary.ferc.gov/eLibrarywebapi/api/). Diese Schnittstelle kann sich ohne Vorankündigung ändern.
Nur öffentliche Dokumente – kein FERC-Login, keine CEII-, privilegierten oder geschützten Inhalte
Seien Sie rücksichtsvoll mit Rate Limits; der Client verteilt Anfragen standardmäßig zeitlich
Nutzen Sie dies für Recherchen zu öffentlich verfügbaren Einreichungen, nicht als Ersatz für offizielle Zugriffsverfahren
Related MCP server: @cyanheads/secedgar-mcp-server
Installation in Claude Desktop (am einfachsten)
Kein Python, kein Terminal, kein JSON. Claude Desktop installiert den Server für Sie.
Installieren Sie Claude Desktop.
Laden Sie
ferc-elibrary.mcpbaus dem neuesten GitHub-Release herunter.Doppelklicken Sie auf die Datei oder ziehen Sie sie in Claude Desktop → Einstellungen → Erweiterungen.
Klicken Sie auf Installieren. Lassen Sie den Download-Ordner unverändert, es sei denn, Sie möchten PDFs an einem anderen Ort speichern.
Fragen Sie Claude in einfacher Sprache, zum Beispiel:
Durchsuche eLibrary nach Kommentaren und Einsprüchen zum Ashokan-Pumpspeicherprojekt im letzten Jahr.
Rufe die Docket-Liste für CP21-470 ab und liste zugehörige Einreichungen auf.
Lade das öffentliche PDF für Accession 20201119-5202 herunter.
Der erste Start kann eine Minute dauern, während Claude Python über uv installiert. Danach startet es schnell. Heruntergeladene Dateien landen in Downloads/ferc-elibrary (oder dem von Ihnen gewählten Ordner). Nur öffentliche Einreichungen.
Falls noch kein Release verfügbar ist, kann ein Maintainer dieselbe Datei erstellen mit:
npx --yes @anthropic-ai/mcpb pack . dist/ferc-elibrary.mcpbDann per E-Mail oder AirDrop dist/ferc-elibrary.mcpb versenden.
Voraussetzungen
Claude-Desktop-Erweiterung: keine auf Ihrem Rechner (Claude verwaltet Python über uv)
uvx / Bibliothek / Mitwirkende: Python 3.12+ und uv
Installation
Endbenutzer (andere MCP-Clients)
Kein Klon erforderlich. Clients starten den Server mit uvx aus Git (siehe MCP-Client-Konfiguration). Ersetzen Sie OWNER durch den GitHub-Besitzer, sobald das Repository veröffentlicht ist:
uvx --from git+https://github.com/OWNER/ferc-elibrary-mcp ferc-elibrary-mcpMitwirkende
git clone https://github.com/OWNER/ferc-elibrary-mcp
cd ferc-elibrary-mcp
uv syncVerwendung der Bibliothek
ELibraryClient ist ein asynchroner Kontextmanager. Verwenden Sie ihn aus Ihrem eigenen Code, ohne den MCP-Server zu starten:
import asyncio
from ferc_elibrary_mcp import ELibraryClient
async def main() -> None:
async with ELibraryClient() as client:
raw, summaries, dates = await client.search(
query="shared facilities agreement",
match="phrase",
)
print(raw.total_hits, dates.source, len(summaries))
if summaries:
filing = await client.get_filing(summaries[0].accession_number)
print(filing.description, filing.url)
asyncio.run(main())Downloads werden unter FERC_DOWNLOAD_DIR abgelegt (Standard: ~/Downloads/ferc-elibrary). Optional: FERC_RATE_LIMIT_SECONDS setzen (Standard: 0.5).
Werkzeuge
Werkzeug | Zweck |
| Stichwort-, Docket-, Accession-, Dokumenttyp-, Kategorie- und Branchensuche. Nur öffentliche Einreichungen. Siehe Datumsfilterung zur Wahl des Datumsfensters. |
| Docket-Liste: zugehörige Einreichungen, Antragsteller, Accession-Nummern. Siehe Docket-Listen vs. Suche für den Unterschied zu |
| Metadaten für eine Accession ( |
| Dateien, die an einer Accession hängen (vor dem Herunterladen aufrufen). |
| Ein öffentliches Anhangsdokument herunterladen und extrahierten Klartext zurückgeben (PDF/DOCX/Text). Verwenden Sie dies, um Einreichungen zu lesen oder zusammenzufassen – |
| Eine öffentliche Einzeldatei, ein ZIP-Archiv einer Accession oder ein erzeugtes PDF unter |
| Bevorzugt für Massendownloads: Viele öffentliche Dateien über Accessions hinweg mit einer Anfrage als ZIP in |
| Nach einem Begriff oder Dokumenttyp suchen und dann zugehörige Einreichungen nach Docket gruppieren (begrenzt auf 10 Dockets × 50 Einreichungen). Optional verwendet |
Privilegierte, geschützte und CEII-Dokumente werden abgelehnt.
Datumsfilterung
Datumsvorgaben sind kontextabhängig, weil ein 60-Tage-Fenster, das auf ein benanntes Docket angewendet wird, stillschweigend den Großteil eines Verfahrens ausblendet:
Aufruf | Angewendetes Fenster |
|
| keins, gesamtes Verfahren |
|
offene Abfrage, keine Datumsangaben | letzte 60 Tage |
|
beliebige explizite | wie angegeben |
|
Jedes Werkzeug, das Datumsangaben akzeptiert – search_filings, collect_related und get_docket – meldet date_range_applied, date_range_source, date_field_applied, results_may_be_date_limited und date_field_filtered_client_side, auch bei leeren Ergebnissen, denn eine leere Ergebnismenge unter einer unbemerkten Standardeinstellung ist der Fall, der am ehesten in die Irre führt. Behandeln Sie total_hits nur dann als vollständige Anzahl, wenn results_may_be_date_limited false ist.
Alle drei ermitteln ihr Fenster über einen gemeinsamen Helfer resolve_date_range und melden es über DateRangeResolution.as_envelope(). Ein Registrierungstest durchläuft die Werkzeugliste und schlägt fehl, wenn ein Werkzeug, das start_date akzeptiert, den Envelope oder einen date_field-Parameter auslässt – so ist ein neues suchartiges Werkzeug ab dem Tag seiner Hinzufügung abgedeckt.
date_field wählt aus, auf welches Datum der Bereich filtert: filed (Standard) oder issued. Verwenden Sie issued für Fristberechnungen: Die Wiederaufnahme nach FPA 313(a) und die meisten von der Kommission gesetzten Kommentar- und Compliance-Fristen laufen ab dem Ausstellungsdatum, und die beiden Daten weichen voneinander ab. Bei ER26-3176 wurde die Accession 20260807-5037 am 08/07 eingereicht, aber am 08/06 ausgestellt – eine Suche nach dem Einreichungsdatum am 08/06 übersieht sie daher. Beide werden von eLibrary serverseitig gefiltert, sodass das Paging exakt bleibt.
Docket-Listen vs. Suche
get_docket und search_filings decken dieselben Einreichungen ab, gelangen aber auf unterschiedlichem Weg zu ihnen, und die Unterschiede werden gemeldet, statt sie selbst entdecken zu müssen.
Eine Zeile pro Einreichung. eLibrary gibt eine Zeile pro Docket-Zuordnung zurück, sodass ein Schriftsatz, der auf
-000,-001und-002lautet, dreimal erscheint und seintotalHitsihn dreimal zählt. Zeilen werden anhand der Accession-Nummer zusammengeführt, jede Zuordnung bleibt indocket_numberserhalten, undcount_basismeldetdistinct_accession. Bei EL25-49 macht das den Unterschied zwischen den von FERC gemeldeten 380 und den 312 Einreichungen aus, die Sie tatsächlich abrufen können.Paging erfolgt clientseitig.
numHitsundpageNumberschneiden die Liste nicht zuverlässig – die Zeilen pro Seite überschreiten das angeforderte Limit und spätere Seiten überlappen sich –, daher wird die Liste einmal abgerufen und lokal paginiert.pageist bei beiden Werkzeugen 1-basiert;page=0wird als Seite 1 akzeptiert.Verfügbarkeit. Die Liste enthält keinen Verfügbarkeitscode, daher kann
get_docketnicht danach filtern und meldetavailability_scope: "all".search_filingsist standardmäßig auf öffentliche Inhalte beschränkt. Eine Docket-Liste kann daher einige privilegierte Einreichungen enthalten, die die Suche auslässt; bei EL25-49 sind das 3 von 312.Sortierung.
get_docketliefert zuerst die ältesten (chronologisch, wie eine Docket-Liste),search_filingszuerst die neuesten. Übergeben Siesort_order="newest_first", um sie anzugleichen.Ausstellungsdaten. Die Liste meldet jedes
issued_dateals die .NET-Null-Sentinel0001-01-01, sodass es als leere Zeichenkette statt als Datum im Jahr 1 ausgegeben wird.date_field="issued"beiget_docketlöst das Fenster über den Such-Endpunkt auf, der echte Ausstellungsdaten enthält, und setztdate_field_filtered_client_side: true.
Versiegelte Gegenstücke
get_filing und list_files melden has_nonpublic_counterpart – ein Signal dafür, dass zu derselben Accession wahrscheinlich eine versiegelte, geschützte oder CEII-Version existiert, also das, für das Sie nach 18 C.F.R. 388.113 Zugang beantragen würden. Es wird aus der Benennungskonvention des Einreichenden abgeleitet (ein Dateiname oder eine Beschreibung mit dem Präfix PUBLIC oder mit REDACTED), daher meldet nonpublic_counterpart_basis den Wert file_naming_convention, um es als heuristisch und nicht als verbindlich zu kennzeichnen. Versorgungsunternehmensnamen wie "Public Service Company" sind ausgeschlossen, um falsch positive Treffer zu vermeiden. Geschützte Inhalte werden nie zurückgegeben, und das Signal fehlt in den Ergebnissen von search_filings bewusst.
Suchpräzision
eLibrary behandelt eine bloße Mehrwortabfrage als unabhängige Begriffe, wodurch die Einreichungen, die die Phrase tatsächlich enthalten, untergehen. Zwei Parameter steuern das:
match:phrase(Standard) erfordert die exakte Phrase,allerfordert jeden Begriff,anyist FERCs lockere Begriffssuche.search_in:both(Standard) durchsucht Beschreibungen und vollständigen Dokumenttext,descriptionstimmt nur mit dem Titel der Einreichung überein,full_textnur mit dem Dokumentkörper.
Suche nach shared facilities agreement in Einreichungen aus 2026:
|
| Treffer |
|
| 5.627 |
|
| 324 |
|
| 65 |
Verwenden Sie search_in="description", wenn eine Phrasensuche weiterhin zu viel Rauschen liefert; die Volltextsuche findet jede beiläufige Erwähnung tief in einem Anhang. Eine eLibrary-Syntax, die Sie selbst schreiben (Anführungszeichen, AND, OR, NOT, NEAR), wird unverändert weitergegeben.
Download-Formate
download_file akzeptiert ein format für eine einzelne Accession:
native(Standard) speichert die eine Datei, die durchfile_ididentifiziert wird.zipbündelt jede Datei dieser Accession.pdffordert eLibrary auf, ein kombiniertes PDF der Accession zu erzeugen.
Für viele Dateien oder viele Accessions verwenden Sie stattdessen download_bundle. Es ruft denselben Zip-&-Download-Endpunkt auf, den die eLibrary-Oberfläche verwendet, wenn Sie den grünen ZIP-Ordner füllen – eine HTTP-Anfrage mit einer Liste von Datei-IDs – statt N× (get_filing + Download + Rate-Limit-Wartezeit). Übergeben Sie eine beliebige Mischung aus accession_numbers, file_ids und/oder docket. Standardmäßig werden die flachen FERC-Namen (20260716-5098_Agreement.pdf) in Ordner umgeschrieben (20260716-5098/Agreement.pdf). Die Obergrenzen betragen standardmäßig 100 Dateien / 500 MB (FERC_MAX_BUNDLE_FILES, FERC_MAX_BUNDLE_BYTES); erhöhen Sie FERC_BUNDLE_TIMEOUT_SECONDS (Standard 300) für sehr große Archive.
collect_related(..., download=True) nutzt diesen Massendownload-Pfad und gibt ein bundle-Feld zurück, das auf das Archiv verweist.
eLibrary kennzeichnet jeden Download als application/octet-stream, daher wird der tatsächliche Typ aus Magic Bytes und der Dateiendung abgeleitet (OOXML-Endungen haben Vorrang vor ZIP-Magic, da .docx selbst ein ZIP ist). Ergebnisse für Einzeldateien melden außerdem expected_size aus den FERC-Metadaten neben den tatsächlich geschriebenen Bytes sowie size_matches_metadata und is_bundle – so fällt ein Bundle, das Sie erhalten, obwohl Sie eine Datei angefordert haben, sichtbar auf und bleibt nicht still. format=zip bei einer Accession mit nur einer Datei entpackt zu dieser Datei und aktualisiert diese Felder entsprechend dem Gespeicherten.
Das Claude-Desktop-Bundle erstellen
Von einem Klon aus, mit verfügbarem Node.js 18+:
npx --yes @anthropic-ai/mcpb validate manifest.json
npx --yes @anthropic-ai/mcpb pack . dist/ferc-elibrary.mcpbDas Bundle verwendet server.type = "uv": Es enthält Quellcode und pyproject.toml, keine ausgelieferte virtuelle Umgebung. Claude Desktop lädt Python und Abhängigkeiten beim ersten Start herunter. CI packt bei jedem Push dieselbe Datei und hängt sie an GitHub Releases an.
MCP-Client-Konfiguration
Claude-Desktop-Nutzer sollten die Ein-Klick-.mcpb-Installation bevorzugen. Das folgende JSON ist für Cursor, Claude Code und andere Clients.
Ersetzen Sie OWNER durch den GitHub-Besitzer dieses Repositorys. Alle Codeausschnitte verwenden portables uvx aus Git – keine absoluten Maschinenpfade.
Standardmäßig werden Downloads in ~/Downloads/ferc-elibrary gespeichert, wenn FERC_DOWNLOAD_DIR nicht gesetzt ist. Setzen Sie FERC_MCP_IDLE_TIMEOUT_SECONDS, um verwaiste stdio-Instanzen zu beenden (siehe Verwaiste Serverprozesse); lassen Sie es weg oder verwenden Sie 0, um sich nie selbst zu beenden (Standard).
Claude Desktop
Fügen Sie Folgendes zu ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) oder der entsprechenden Konfiguration von Claude Desktop auf Ihrem Betriebssystem hinzu:
{
"mcpServers": {
"ferc-elibrary": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/OWNER/ferc-elibrary-mcp",
"ferc-elibrary-mcp"
],
"env": {
"FERC_DOWNLOAD_DIR": "/Users/YOU/Downloads/ferc-elibrary",
"FERC_MCP_IDLE_TIMEOUT_SECONDS": "14400"
}
}
}
}Verwenden Sie einen absoluten Pfad für FERC_DOWNLOAD_DIR (expandieren Sie ~ selbst). Claude Desktop ist eine GUI-Anwendung und expandiert möglicherweise weder ~ noch übernimmt es das PATH Ihrer Shell; stellen Sie sicher, dass uvx in einem PATH liegt, den die Anwendung sehen kann (z. B. indem Sie uv systemweit installieren oder den vollständigen Pfad zu uvx angeben).
Beenden Sie Claude Desktop vollständig und öffnen Sie es erneut. Bestätigen Sie den Server unter Einstellungen → Entwickler.
Cursor
Fügen Sie Folgendes zu .cursor/mcp.json in einem Projekt oder Ihrer Benutzer-MCP-Konfiguration hinzu:
{
"mcpServers": {
"ferc-elibrary": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/OWNER/ferc-elibrary-mcp",
"ferc-elibrary-mcp"
],
"env": {
"FERC_DOWNLOAD_DIR": "/Users/YOU/Downloads/ferc-elibrary",
"FERC_MCP_IDLE_TIMEOUT_SECONDS": "14400"
}
}
}
}Claude Code
Projektbereich (.mcp.json im Projektstamm) oder Benutzerbereich (claude mcp add / ~/.claude.json):
{
"mcpServers": {
"ferc-elibrary": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/OWNER/ferc-elibrary-mcp",
"ferc-elibrary-mcp"
],
"env": {
"FERC_DOWNLOAD_DIR": "${HOME}/Downloads/ferc-elibrary",
"FERC_MCP_IDLE_TIMEOUT_SECONDS": "14400"
}
}
}
}Oder über die CLI:
claude mcp add --scope user ferc-elibrary -- \
uvx --from git+https://github.com/OWNER/ferc-elibrary-mcp ferc-elibrary-mcpBeispiel-Prompts
Durchsuchen Sie die eLibrary nach Kommentaren und Einsprüchen zum Pumpspeicherprojekt Ashokan aus dem letzten Jahr.
Rufen Sie die Docket-Übersicht für CP21-470 ab und listen Sie zugehörige Einreichungen auf.
Finden Sie Order/Opinion-Veröffentlichungen in der Elektrizitätsbranche aus Januar 2024 und sammeln Sie zugehörige Docket-Einreichungen.
Laden Sie das öffentliche PDF für die Accession 20201119-5202 herunter.
Test mit dem MCP Inspector
In einem Klon des Projekts:
npx @modelcontextprotocol/inspector uv run ferc-elibrary-mcpRufen Sie search_filings mit docket P-15056-000 und einem start_date / end_date um den 2020-11-19 herum auf, um einen bekannten öffentlichen Treffer zu bestätigen.
Tests
uv run pytest
uv run pytest -m live # optional smoke test against the live public APIEinschränkungen
Nur öffentliche Dokumente. Kein FERC-Login, kein CEII, keine privilegierten oder geschützten Dateien.
Dateibytes werden auf die Festplatte geschrieben und nicht über die MCP-Tool-Antwort zurückgegeben.
collect_relatedbegrenzt, wie viele Dockets und Dateien abgerufen werden, sodass eine breite Abfrage nicht Tausende von Einreichungen in den Kontext kippen kann.Das Backend ist undokumentiert und liegt hinter einem Proxy, der zeitweise 502/503/520 zurückgibt. Vorübergehende 5xx-Antworten werden mit Backoff bis zu dreimal wiederholt.
FERC gibt für einige fehlerhafte Payloads HTTP 200 mit
success: falseund einer .NET-Exception-Zeichenfolge zurück. Diese werden als Fehler gemeldet, anstatt stillschweigend null Treffer zurückzugeben.
Verwaiste Serverprozesse
Manche MCP-Clients (insbesondere Claude Desktop) starten gelegentlich zwei stdio-Server innerhalb einer Sekunde nacheinander und kommunizieren nur mit einem von ihnen. Sie schließen möglicherweise das stdin der verwaisten Instanz nicht, sodass dieser Prozess nie ein EOF sieht und für immer im Leerlauf bleibt — in der Praxis bleibt ein Paar pro Tag übrig, und Tool-Aufrufe, die an eine veraltete Instanz geroutet werden, hängen, bis der eigene Timeout des Clients greift, anstatt fehlzuschlagen.
Der Server selbst trägt keine Schuld: Er beendet sich sauber bei stdin-EOF (Exit-Code 0) und bei SIGTERM. Eine verwaiste Instanz hat schlicht keine Möglichkeit zu bemerken, dass niemand zuhört.
Setzen Sie FERC_MCP_IDLE_TIMEOUT_SECONDS, damit sich eine Instanz, die so lange keine Nachrichten erhalten hat, selbst per SIGTERM beendet. Jede Anfrage setzt den Timer zurück, sodass ein genutzter Server unbeeinflusst bleibt; nur eine vollständig verwaiste Instanz wird beendet. Die Option ist standardmäßig deaktiviert (0), da ein gesunder, aber ungenutzter Server ebenfalls beendet würde und die Wiederherstellung dann davon abhängt, dass der Client ihn neu startet. Die obigen Beispielkonfigurationen setzen 4 Stunden, deutlich länger als jede Unterbrechung in einer aktiven Sitzung.
Um verwaiste Prozesse manuell zu finden und zu beenden:
ps -eo pid,etime,command | grep '[f]erc-elibrary-mcp'
kill -TERM <pid> # they are idle, not wedged; no -9 neededLizenz
MIT — siehe LICENSE.
Available Tools
13 toolscache_statusC
Report what the document store holds for a docket or accession.
| Name | Required | Description | Default |
|---|---|---|---|
| docket | No | ||
| accession | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only inspection via 'Report', but does not state whether it mutates anything, whether both parameters may be supplied together, what happens when both are null, or what 'holds' concretely means (e.g., existence, metadata, document segments).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler, and the core idea is front-loaded. It is efficient, though brevity comes at the cost of missing operational context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists so return-value details need not be in the description, the tool is underspecified for a user trying to call it correctly. Key invocation constraints—parameter optionality, exclusivity, and what a cache status report actually contains—are absent, making this incomplete for reliable tool selection and use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the bare schema. It adds only the relationship 'docket or accession', but does not explain the expected identifier formats, whether at least one is required, whether they are exclusive, or what each parameter affects in the report.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a specific action ('Report') and a specific resource ('what the document store holds for a docket or accession'), which distinguishes it as a cache-status inspection tool among siblings like get_docket and sync_docket. It does not explicitly name a sibling alternative, but the purpose is not tautological or vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives such as get_docket, sync_docket, or list_files. The intended use case (checking cached holdings before fetching or syncing) is only weakly implied, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
download_bundleA
Zip many public files into one archive under FERC_DOWNLOAD_DIR/bundles.
Prefer this over repeated download_file calls. eLibrary's Zip & Download accepts many file IDs in a single request (including across accessions), so one call replaces N metadata lookups + N downloads + N rate-limit waits.
Provide any combination of accession_numbers (all public files on each),
file_ids (exact attachments), and/or docket (public files found via search
on that docket). Default organize_by_accession=true rewrites FERC's flat
accession_filename members into accession/filename folders.
Caps: 100 files and 500 MB by default (FERC_MAX_BUNDLE_FILES / FERC_MAX_BUNDLE_BYTES). Privileged, protected, and CEII accessions — and accessions absent from public search — are skipped and listed in skipped_accessions with a reason and category (restricted vs not_found). Does not return file bytes.
| Name | Required | Description | Default |
|---|---|---|---|
| docket | No | ||
| file_ids | No | ||
| accession_numbers | No | ||
| organize_by_accession | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden, and it does so thoroughly: it discloses filesystem side effects (writing under FERC_DOWNLOAD_DIR/bundles), default folder reorganization, file/size caps, the skipping behavior for restricted/not-found accessions with reasons and categories, and the fact that it does not return file bytes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but every sentence adds value: purpose, alternative comparison, parameter semantics, caps, skip behavior, and the no-bytes return caveat. It is front-loaded with the core purpose before diving into details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given four optional parameters, no annotations, and no schema descriptions, the description covers all necessary operational context: selection semantics, side effects, limits, failure handling, and return caveats. The presence of an output schema means return-field detail is not required in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates by explaining each parameter: accession_numbers select all public files on each accession, file_ids target exact attachments, docket selects public files via search, and organize_by_accession controls folder structure with a clear default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Zip many public files into one archive under FERC_DOWNLOAD_DIR/bundles.' It also explicitly differentiates itself from the sibling tool download_file by saying 'Prefer this over repeated download_file calls,' making the tool's distinct role unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states when to use this tool ('Prefer this over repeated download_file calls') and enumerates valid input combinations. It does not explicitly spell out exclusions like 'use download_file for a single file or restricted accessions,' but the restricted/not-found skipping behavior implies those cases are not this tool's purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
download_fileA
Download a public eLibrary file to FERC_DOWNLOAD_DIR.
Does not return file bytes. Privileged, protected, and CEII documents are refused. Call list_files first to pick a file_id.
format=native saves that one original file and is the default. format=zip asks eLibrary for every file on the accession as one archive; if the accession has a single attachment, the archive is unwrapped to that file and content_type / is_bundle / expected_size describe the saved document. format=pdf asks eLibrary to generate a combined PDF of the whole accession.
The result reports expected_size from FERC's metadata alongside the byte count actually written, plus size_matches_metadata and is_bundle, so a mismatch between the file you asked for and the artifact you got is visible.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | native | |
| file_id | No | ||
| accession_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the burden and does so admirably. It discloses the side effect of saving to FERC_DOWNLOAD_DIR, states that file bytes are not returned, explains refused document types, and reveals how format choices change the saved artifact and result metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed yet tightly organized, with each paragraph serving a distinct purpose: primary action, key caveats, format semantics, and result interpretation. No sentence feels redundant or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, the description covers prerequisites, refusals, format variants, side effects, return-value semantics, and mismatch detection. The presence of an output schema reduces the need to describe return fields, yet the description still adds useful interpretive context about size_matches_metadata and is_bundle.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It thoroughly explains the format enum values, their defaults, and their behavioral differences, and it explains file_id's role via the list_files prerequisite. accession_number is not explicitly explained, though the tool name and context make it reasonably inferable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Download a public eLibrary file to FERC_DOWNLOAD_DIR.' It clearly distinguishes this tool from siblings by focusing on a single file download and by describing the non-return of file bytes, making its role unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit operational guidance: call list_files first to pick a file_id, and it warns that privileged/protected/CEII documents are refused. It does not explicitly compare against the sibling download_bundle, so the choice between this tool and that alternative is somewhat left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_docketA
Return the docket sheet: related filings, applicants, and accession numbers.
Docket numbers look like CP21-470, ER11-4046, or P-15056-000. Subdockets can be All or a comma-separated list such as 000,001.
page is 1-indexed, matching search_filings. page=0 is accepted as page 1.
One row per filing: eLibrary returns one row per docket association, so a pleading captioned to -000, -001 and -002 arrives three times. Rows are merged on accession number and every association is listed in docket_numbers, so total_hits counts filings you can actually retrieve. count_basis reports distinct_accession to make that explicit.
Scope differs from search_filings in one way worth knowing: the docket sheet carries no availability code, so it cannot filter by availability and reports availability_scope "all". search_filings is public-only by default, so a docket sheet may list a few privileged filings that search omits.
sort_order defaults to oldest_first, the chronological order of a docket sheet. search_filings returns newest first. Pass newest_first to match it.
date_field and the date envelope behave as in search_filings. Since a docket number is always supplied, no 60-day default is ever applied here. An issued-date window is applied to rows after retrieval, reported via date_field_filtered_client_side.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| end_date | No | ||
| date_field | No | filed | |
| sort_order | No | oldest_first | |
| start_date | No | ||
| subdockets | No | All | |
| docket_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so exceptionally. It discloses row duplication and merging by accession number, total_hits semantics, count_basis=distinct_accession, availability_scope='all', the absence of a 60-day default, client-side date filtering, and page=0 handling. This is far more transparent than most tool descriptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but every sentence earns its place. It is organized into logical chunks: core purpose, docket/subdocket format, pagination, row-merging behavior, comparison to search_filings, sort order, and date behavior. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description need not explain return values. It covers edge cases (page=0, subdocket lists, multi-docket filings, privileged filings, client-side date filtering) and differentiates behavior from a key sibling. An agent has enough to call this tool correctly and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains docket_number format, subdockets values, page indexing, sort_order meaning and default, and date_field/envelope behavior. The only notable omission is the limit parameter, which is left to inference, but the overall parameter guidance is strong.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource: 'Return the docket sheet: related filings, applicants, and accession numbers.' It also gives concrete docket number examples and clearly differentiates itself from search_filings by scope and behavior. An agent can confidently identify this tool as the one that retrieves a docket sheet by docket number.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly contrasts get_docket with search_filings: availability handling, sort order defaults, and date-field behavior. It implies the primary use case is when you have a docket number. It does not include an explicit 'use this when / use search_filings when' rule, but the comparisons provide strong routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_document_outlineB
Return PDF bookmarks or a heuristic section map for a stored filing.
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | ||
| accession_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It does convey the key fallback behavior: return PDF bookmarks if available, otherwise a heuristic section map. It does not, however, state side effects, error conditions, or whether the operation is read-only, though 'Return' implies non-mutating.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with the action and output type, and no filler. This is as concise as possible while still conveying the tool's core behavior and fallback.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The presence of an output schema covers return-value details, and the two required parameters are simple strings. Still, the description lacks parameter semantics and usage guidance, so the definition is only minimally complete for an agent choosing among siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description needed to explain what accession_number and filename mean, but it does not. The phrase 'stored filing' offers only weak context; the parameter names themselves are doing the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description names a specific verb ('Return') and a precise resource: 'PDF bookmarks or a heuristic section map for a stored filing.' This makes the output clear and distinguishes the tool from siblings like get_filing_text or read_document, which return content rather than a document outline.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description gives no explicit when-to-use advice and does not mention any sibling alternative, so an agent must infer from the tool name and output type when to select it over get_filing_text or search_within_document. There are no exclusion conditions or prerequisites stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_filingA
Fetch metadata for one filing by accession number (YYYYMMDD-NNNN).
has_nonpublic_counterpart signals that a sealed, protected, or CEII version likely exists on the same accession, which is what you would move for access to under 18 C.F.R. 388.113. It is inferred from filer naming convention ("PUBLIC" or "REDACTED" in a file name), so nonpublic_counterpart_basis reports it as file_naming_convention rather than authoritative metadata. No protected content is ever returned.
| Name | Required | Description | Default |
|---|---|---|---|
| accession_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. It discloses a meaningful behavioral limitation ('No protected content is ever returned') and explains that has_nonpublic_counterpart is inferred from filer naming conventions rather than authoritative metadata, which is important for interpreting results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the core purpose, and every sentence adds value: the first states what the tool does, the second explains the nonpublic_counterpart semantics, and the third explicitly reassures about protected content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single required parameter, an output schema, and one key behavioral caveat, the description is largely complete. It explains the non-authoritative nature of an important field. It could be more complete by explicitly naming get_filing_text as the tool for content, but that is not essential for invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only declares accession_number as a string with no description, giving 0% schema coverage. The description compensates by providing the exact expected format ('YYYYMMDD-NNNN'), which is crucial for calling the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Fetch'), the resource ('metadata for one filing'), and the key identifier ('accession number (YYYYMMDD-NNNN)'). This distinguishes it from sibling tools like get_filing_text by emphasizing 'metadata' rather than content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving metadata for a single filing and explicitly notes when a nonpublic counterpart would be relevant (moving for access under 18 C.F.R. 388.113). However, it does not explicitly contrast with search_filings or get_filing_text, leaving some routing decisions to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_filing_textA
Deprecated alias for bounded read_document.
Returns at most max_chars of extracted text and reports total_chars when truncated. Prefer get_document_outline, search_within_document, and read_document for large filings.
| Name | Required | Description | Default |
|---|---|---|---|
| file_id | No | ||
| max_chars | No | ||
| accession_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the truncation behavior ('at most max_chars', 'reports total_chars when truncated') and the deprecated status, which is meaningful behavioral context. It does not mention side effects or permissions, but the read-only nature is clear enough for a deprecated text-retrieval alias.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. It front-loads the deprecation and core behavior, then provides routing guidance to alternatives. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists, so return-value details are not required. The description covers deprecation, truncation, and alternative tools well, but incomplete parameter semantics for file_id and accession_number prevent full completeness. It is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter meaning. It only explains max_chars; the meanings of accession_number and file_id, and their relationship, are left undocumented. This is a notable gap for an agent trying to call the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a deprecated alias for read_document and specifies the exact behavior: 'Returns at most max_chars of extracted text.' It names the resource (filing text), the operation (bounded read), and distinguishes itself from siblings by framing it as deprecated and bounded.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly steers agents away from this tool for large filings by recommending get_document_outline, search_within_document, and read_document. However, it does not clearly describe when this tool should still be used, only implies it may be acceptable for smaller bounded reads.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_filesA
List files attached to an accession. Call this before download_file.
See get_filing for what has_nonpublic_counterpart means.
| Name | Required | Description | Default |
|---|---|---|---|
| accession_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden of behavioral disclosure. It reveals the operation is a listing action and hints at has_nonpublic_counterpart semantics only via cross-reference, but it does not state whether the call is read-only, what metadata is returned, or whether pagination or limits apply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact: two short sentences with no filler. The first sentence states the action, and the second efficiently redirects to get_filing for a relevant term instead of duplicating context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter listing tool with an output schema available, the description covers the core action and workflow ordering. It is close to sufficient, though it would benefit from a brief note on expected file metadata or read-only behavior since annotations are absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no description for accession_number (0% coverage), and the description only ties it to 'an accession' and the download workflow. This adds some meaning beyond the bare parameter name, but it does not specify the expected format or how to obtain the accession number.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and a concrete resource ('files attached to an accession'), making the tool's function immediately clear. It also differentiates from download_file by positioning itself as the step before downloading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'Call this before download_file,' which gives clear sequencing guidance. It also points to get_filing for understanding has_nonpublic_counterpart. It does not fully enumerate when not to use other sibling tools, so it stops short of a complete routing guide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_documentA
Return bounded plain text from a cached filing attachment.
Never returns the full document unless it fits within max_chars. Responses include total_chars, truncated, and next_char_start / next_page when clipped.
| Name | Required | Description | Default |
|---|---|---|---|
| pages | No | ||
| char_end | No | ||
| filename | Yes | ||
| max_chars | No | ||
| char_start | No | ||
| accession_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states the truncation behavior, the guarantee that the full document is never returned unless it fits within max_chars, and the response metadata (total_chars, truncated, next_char_start/next_page) when clipped. This is strong, concrete behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three tightly scoped sentences with the primary action front-loaded. Every sentence earns its place: the return type and source, the critical size limitation, and the response navigation contract.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema covers return-value details, and the description provides solid behavioral context. However, the 6-parameter schema has zero description coverage and the description compensates only for max_chars, so an agent still lacks sufficient guidance on pagination/range parameters and how this tool compares to siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% across 6 parameters, and the description only adds meaning for max_chars. It does not explain pages, char_start, char_end, accession_number, or filename, leaving key range-selection and document-identification semantics undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Return bounded plain text from a cached filing attachment,' which names a specific verb, resource, and scope. The 'Never returns the full document' constraint clearly differentiates it from sibling tools like get_filing_text, which likely returns complete document text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied: use this when you need bounded plain text from a cached filing attachment. However, it does not explicitly name alternatives or state when not to use this tool, so the agent must infer routing decisions from sibling names and the bounded-text behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_filingsA
Search public FERC eLibrary filings. Public documents only.
Use for keyword/term search, docket prefix (CP, ER11-4046), accession numbers, or document types such as Order/Opinion, Comments/Protest, or Application/Petition/Request.
Date defaulting: when docket or accession_number is supplied, no date filter is applied and the whole proceeding is searched. For an open-ended query with no dates, the last 60 days is used to keep the result set manageable. Every response reports date_range_applied, date_range_source (explicit/default_60_day/none), and results_may_be_date_limited, so check those before treating total_hits as a complete count.
date_field selects which date start_date and end_date filter on. Use "issued" when computing deadlines: FPA 313(a) rehearing and most Commission-set comment and compliance clocks run from issuance, not from the filed date, and the two differ. Orders are generally best searched by issuance.
match controls how a multi-word query is interpreted. "phrase" (default) requires the exact phrase and is what you want when looking for a named agreement or document. "all" requires every term anywhere. "any" is FERC's loose term matching, which returns high volume and low precision.
search_in controls where the query is matched. "both" (default) covers descriptions and full document text. "description" is far more precise because it matches the filing title rather than any passing mention deep in an attachment. Use it when a phrase search still returns too much noise.
You may also pass eLibrary syntax directly (quotes, AND, OR, NOT, NEAR); it is forwarded unchanged.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| match | No | phrase | |
| query | No | ||
| docket | No | ||
| category | No | ||
| end_date | No | ||
| industry | No | ||
| search_in | No | both | |
| date_field | No | filed | |
| start_date | No | ||
| document_type | No | ||
| accession_number | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden and meets it well. It reveals the default 60-day window for open-ended queries, the no-date-filter behavior when docket or accession_number is supplied, and the presence of response flags like date_range_applied and results_may_be_date_limited. It also discloses nuanced behaviors around date_field and match modes that an agent would otherwise have to discover by trial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with a clear opening and topic-focused paragraphs, each sentence adds useful information. The opening repeats 'public' twice ('public FERC eLibrary filings' and 'Public documents only'), which is minor redundancy; otherwise it is appropriately dense for a 13-parameter search tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex search tool with no annotations, this description is unusually complete: it covers search scope, date defaults, parameter behavior, and response caveats. An output schema exists to define the return shape, so the description provides enough context for correct invocation without missing essential operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, and it does. It explains docket, accession_number, date_field, match, search_in, and document_type with examples and usage guidance. Only page, limit, category, and industry are not directly addressed, but the most consequential parameters are richly specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Search public FERC eLibrary filings.' It also scopes the tool with 'Public documents only' and lists concrete supported query keys (keywords, docket prefix, accession numbers, document types), making it clearly distinguishable from siblings like get_filing or list_files.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives clear context on how to search: which fields to use, date defaulting behavior, and trade-offs between match and search_in modes. It stops short of explicitly saying when not to use this tool versus a sibling like get_filing, so it lacks explicit when-not/alternatives guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_within_documentB
Search extracted text for a query and return passages with page/char offsets.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| filename | Yes | ||
| max_hits | No | ||
| accession_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses the core read-only search behavior and the output shape, but it does not mention side effects, extraction prerequisites, pagination, max_hits behavior, or edge cases. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with a leading verb and no filler. Every phrase adds meaning: the search action, the input type (extracted text), and the output (passages with offsets).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four parameters with no schema descriptions and no annotations, so more context is required. The output schema covers the return shape, but the missing parameter semantics and lack of usage guidance leave the description incomplete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only clarifies 'query' by referring to it as a query. It does not explain accession_number, filename, or max_hits, leaving the agent to guess why both identifiers are required and how max_hits limits results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a specific verb ('Search'), a resource ('extracted text'), and an explicit output ('passages with page/char offsets'). This makes it clear what the tool does and distinguishes it from siblings like get_filing_text and read_document, which return full text rather than matched passages with offsets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to prefer this tool over alternatives. It does not mention that it is for searching within a single document rather than across filings, and it does not contrast with siblings such as search_filings, get_filing_text, or read_document.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sync_docketB
Incrementally fetch accessions missing from the document store for a docket.
| Name | Required | Description | Default |
|---|---|---|---|
| docket_number | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It mentions 'incrementally' and the scope 'missing from the document store,' but it does not state whether the tool writes to or mutates the document store, whether it is idempotent, or whether it may be a long-running operation. The wording is ambiguous about side effects, which is a significant gap for a tool named 'sync_docket.'
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of twelve words, front-loaded with the verb and object. Every word contributes meaning: 'incrementally' clarifies scope, 'missing from the document store' specifies the target set, and 'for a docket' ties it to the parameter. There is no redundant language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists, so return values need not be explained. However, the absence of annotations and the terse description leave important operational context untold: whether the tool mutates the document store, what 'accessions' means in this domain, how 'incrementally' is determined, and whether a prior cache or docket fetch is required. An agent could not fully assess side effects or prerequisites from this description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one required parameter (docket_number) with zero description coverage. The tool description's 'for a docket' implicitly identifies docket_number as the target docket, adding some contextual meaning. However, it does not specify the expected format, example values, or any constraints, so it only partially compensates for the missing schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('fetch') and a precise resource ('accessions missing from the document store for a docket'). It clearly communicates an incremental sync operation, which is distinct from the other listed tools like get_docket or get_filing. It does not explicitly name sibling alternatives, so it stops short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'incrementally fetch accessions missing' implies a backfill/sync scenario, giving some sense of when to use this tool. However, it does not explicitly state when to prefer this tool over alternatives such as get_docket or cache_status, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Most tools target distinct levels of the eLibrary: search, docket metadata, accession metadata, attachment listing, downloads, and document text. The deprecated get_filing_text alias overlaps with read_document and could be confused with get_filing, and collect_related combines search and docket listing, but the descriptions clarify the intended boundaries.
Almost every tool follows a verb_noun snake_case pattern such as search_filings, get_docket, and download_file. cache_status breaks the verb pattern, collect_related uses an adjective-like object, and get_filing_text is a stale alias, so the naming is mostly but not fully consistent.
13 tools is within the well-scoped range and covers search, metadata access, file listing, downloads, bundle downloads, document text analysis, and cache management. The deprecated get_filing_text alias and the more internal cache_status/sync_docket tools add slight weight, but the set does not feel bloated.
The tools cover the public-filing lifecycle end to end: docket and accession search, metadata retrieval, file listing, single and bundle download, extracted-text reading, within-document search, outlines, and cache synchronization. No obvious operations are missing for the stated FERC eLibrary retrieval domain.
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