Archival Summary
🤖 AI Drafted (Not reviewed)
Compose nine-section archival summary for a folder (leaf node of the Catalogue workflow)
|
|
| Tool id |
catalogue |
| Category |
llm |
| Uses a language model |
yes |
| Needs a generative model |
no |
| Runs over many items |
no |
| Item handling |
batch |
| Structured output |
yes |
| Human-verified |
not yet |
What it reads
| Port |
Type |
Required |
What it is |
Text (text) |
text |
no |
Aggregated TRANSCRIPTION text — wire from aggregate.text (per-file transcriptions joined), NOT from the merge of cleanup outputs. The narrative LLM reads this as source material; pointing it at cleaned entity lists makes it summarise the cleanup output instead of the documents. |
Data (data) |
any |
yes |
Dependency-only input. Its value is ignored; it exists to sequence catalogue after its upstream — canonical entity cleanup in the full preset, the source node in ‘Catalogue Description’. |
Context (context) |
any |
no |
Previous text/transcription |
Metadata (metadata) |
json |
no |
Existing metadata |
Documents (documents) |
json |
no |
Document metadata |
What it emits
| Port |
Type |
Required |
What it is |
Text (text) |
text |
— |
Raw text response |
Value (value) |
any |
— |
Parsed value |
Texts (texts) |
array |
— |
Per-item texts |
Values (values) |
array |
— |
Per-item values |
Results (results) |
json |
— |
Full results |
Records (records) |
array |
— |
Per-document text records [{doc_id, text}, …]. |
Artifacts (artifacts) |
json |
— |
Artifact IDs |
Options
| Option |
Type |
Default |
What it does |
ambiguous_min_items |
integer |
25 |
Minimum child documents before ambiguity HITL can trigger. |
choices |
array |
— |
Valid choices. (Not shown in the editor.) |
chunk_size_chars |
integer |
0 |
Chunk large input text above this character budget (0=auto). |
claim_context_caps |
object |
{} |
Per-section caps for the entity-context block fed to the narrative LLM. Keys: people, places, organizations, events, dates, keywords. Each value is the max items to include before the list is truncated with ‘(… +N more)’. Defaults: people=30, places=20, organizations=15, events=15, dates=30, keywords=30. Override only the sections you want to change. Useful on dense folders (100+ contributors) or sparse letters where you want to dial cap up/down. (#865). |
hitl_on_ambiguous_grouping |
boolean |
no |
Pause for confirmation when case grouping appears ambiguous. |
match_mode |
string |
prefer |
Match mode. One of: prefer, strict, inform. |
max_items |
integer |
10 |
List max items. |
max_tokens |
integer |
8192 |
Max response. |
max_words |
integer |
50 |
Word limit. |
metadata_field |
string |
— |
Save to field. |
model_name |
string |
— |
Model name. |
output_format |
string |
text |
Response format. One of: text, boolean, choice, number, words, list, json. |
output_language |
string |
auto |
Output language. ‘auto’ detects from the source text (English / Spanish today); explicit names like ‘English’ or ‘Spanish’ pin the language regardless of input. |
prompt |
string |
— |
Custom prompt. |
provider_name |
string |
— |
LLM provider. One of: openai, anthropic, google, ollama, lmstudio, groq, together, deepseek, mistral, openrouter, dashscope, xai, perplexity, fireworks, deepl. |
quality_gate |
boolean |
yes |
Stop the run if output is unreadable. |
reference_values |
object |
— |
Known values to match. (Not shown in the editor.) |
save_to_db |
boolean |
yes |
Save to library. |
save_to_file |
boolean |
no |
Export to file. |
temperature |
number |
0.7 |
Creativity. |
thinking_mode |
string |
off |
Chain-of-thought reasoning depth. One of: off, short, medium, long. |
The prompt it sends
This is what the tool asks a model, with every option left at its default. Changing the options above changes this text.
You are an archivist. Write a catalogue entry in English for what
these documents CONTAIN. One paragraph, plain prose. NO title, NO heading,
NO label, NO bold, NO Markdown, NO bullets, NO JSON. Start directly with
the document type in the source's own vocabulary (a deed, lawsuit, letter,
report, chapter, photograph, etc.).
LENGTH. The entry is NEVER longer than 200 words. For a long file or a
folder, aim for 150-200 words. Only a short formulaic record (parties,
object, price, terms) may be shorter, 30-100 words. Never pad: stop when
the records are described.
Say who, what, when and where, as the records say it: subject and actors
first, then concrete dates, places, sums, occupations, claims and outcomes.
Use evidentiary verbs: contains, records, states, alleges, describes, names,
signs. Attribute what a record says ("states that ..."). Keep names, dates,
sums, places and accents verbatim, and keep every [ilegible] / [uncertain]
marker as written. Frame any racial, caste or status label as the source's:
"(described as ...)".
NO ANALYSIS. Do not say what a record suggests, reveals, shows about or
means. Do not give significance, themes, mood or a purpose the record does
not state. Never use: suggests, likely, appears to, reveals, highlights,
sheds light, provides insight, important, notably. Do not invent names,
dates, places or facts.