rpg-summarizer

name	rpg-summarizer
description	Generates a narrative session recap from a transcript, using campaign context. Processes the transcript in sequential subagent chunks to preserve chronological order.

RPG Summarizer

Convert a raw transcript into a narrative story using the campaign's writing style. The transcript is split into ~800-line chunks processed by dedicated subagents in sequence. Each subagent receives only its chunk plus a rolling summary of prior events, so events can never be reordered or confused across the session.

Step 1: Context Loading

• Run the glossary extractor:

  .venv/bin/python scripts/extract_glossary.py content/assets/sessions/{NNN}/transcript.txt
  

  Save the stdout — this is the canonical-names glossary for this session. It lists every NPC/location/item/lore entry from the wiki that appears (by phonetic prefix) in the transcript, plus aliases harvested from [[Canonical|Alias]] wikilinks. Embed this glossary into every chunk prompt verbatim.
• Read .agent/skills/rpg-summarizer/resources/phonetic_corrections.md — a curated list of ASR misspellings (e.g. Pytrion → Raspytrion). Embed verbatim into every chunk prompt too.
• Read the last 3 session files in content/01-Sessions/ for narrative arc continuity.

You do NOT need to pre-load the full transcript into the orchestrator's context — the chunk subagents read their own slices.

Step 2: Load Style Prompt

Read .agent/skills/rpg-summarizer/resources/summary_prompt.txt in full. You will embed its entire content into every subagent prompt below — it defines tone, character names, section formatting, and language style, plus anti-hallucination guardrails and the IC/OOC distinction.

Step 3: Chunk the Transcript

Determine the total line count of the transcript via wc -l. Divide into sequential chunks of ~800 lines. Record each chunk's start line and end line.

Step 4: Sequential Subagent Processing

Process chunks strictly one at a time — never in parallel, since each depends on the previous result.

Start with rolling_summary = "".

For each chunk, spawn a subagent with this prompt:

---

You are a narrative summarizer for a Polish D&D campaign session. This is chunk [N of TOTAL].

Style & Rules

[paste full content of summary_prompt.txt here]

Canonical Names Glossary

[paste full stdout of extract_glossary.py here]

Phonetic Corrections

[paste full content of phonetic_corrections.md here]

Context from previous chunks

[If rolling_summary is empty:] This is the beginning of the session. No prior context.

[If rolling_summary is not empty:] Dotychczasowe wydarzenia sesji: [rolling_summary]

Continue the narrative from where these events left off. Do not re-introduce characters or locations already established. Do not recap what has already happened.

Transcript excerpt

Read lines [START]–[END] of content/assets/sessions/{NNN}/transcript.txt (use Read tool with offset: [START-1] and limit: [END-START+1]). Read ONLY this slice.

Your Output

Return exactly two labeled blocks and nothing else:

NARRATIVE

[1–4 narrative ### sections in Polish covering this chunk's events, following the style rules above. Each section has a descriptive heading and 1–3 rich paragraphs.]

ROLLING_SUMMARY

[3–5 bullet points in Polish: key events, decisions, revelations, and the party's location/situation at the end of this chunk. Be specific — this is the only context the next chunk will receive.]

---

After each subagent completes:

• Append its NARRATIVE block to your running output.
• Replace rolling_summary with its ROLLING_SUMMARY block for the next iteration.

Step 5: Validation Pass

Before returning the assembled draft, run one final subagent as a fact-checker. Its job is to spot fabrications and propagated errors that slipped past the chunk subagents.

Spawn a subagent with this prompt:

---

You are a fact-checker for a Polish D&D session recap draft. Your job is to find specific factual claims that are NOT supported by the transcript, and propagated hallucinations.

Inputs

• Draft to verify: [paste the assembled NARRATIVE here]
• Transcript: content/assets/sessions/{NNN}/transcript.txt ([N] lines)
• Canonical glossary: [paste glossary]
• Phonetic corrections: [paste corrections]

Method

For each claim in the draft that names a specific spell, item, NPC, number, or "first/last/never" superlative:

1. Find a transcript line that supports it (use Grep/Bash to search by keyword).
2. If you cannot find supporting evidence, flag it.

Also flag:

• Names not in the canonical glossary (likely ASR misspellings the chunk subagent didn't correct)
• Items/buffs/effects that come from a previous session and may have expired
• Direction-of-spell errors (who cast on whom)
• Mechanical numbers narrated as in-fiction events (e.g. "advantage k8")

Output

Return a list, one finding per line:

• LINE_OR_QUOTE | what's wrong | suggested fix (or "remove")

If nothing is wrong, return exactly: NO ISSUES.

Do not rewrite the draft. Do not be conservative — flag anything you cannot verify.

---

The orchestrator then applies (or asks the user about) each finding before saving the file.

Step 6: Output

Concatenate all NARRATIVE blocks in chunk order. Do not reorder sections. Apply validation findings.

• Constraint: No [[wiki links]] yet — plain text only.
• Constraint: Follow the structure from templates/Session.md.
• Return the complete Markdown. Do not save to a file (the workflow handles that).