Storytelling Skill · v1

Three traditions.
One skill tree.

Storymakers method · consulting deck craft · contrarian playbook — three traditions distilled into one canon, indexed by role not folder. 110 resources across 6 areas, read by your AI as a skill.

  • 110 resources
  • 6 areas
  • 13 categories
  • 24 MCP tools
canonical surface storytelling://

Resource URIs are organized by role, not by physical folder: method, canon, craft, applications and examples.

source of truth MCP + corpus

Agents read the live canon from Postgres and the fused prose corpus from the same server package.

viewer-ready DeckJson aware

The skill includes the deck preview contract, slide descriptions and playbook comparison workflow.

Browse by area

6
one skill tree, multiple operating lenses

Skill Orchestrator

3 resources

How the Storytelling skill asks for canon, resources, deck evidence and output contracts.

Method

59 resources

Storymakers operating guidance: process, agents, checklists, storytelling moves and playbook examples.

Canon

12 resources

Reusable abstractions: arcs, loops and application patterns that should converge with Postgres canon.

Craft

10 resources

Slide, prose, rhythm and composition techniques for making the canon visible on the page.

Applications

25 resources

Consulting, activist, valuation, campaign and research-note use cases built from the shared canon.

Examples

1 resources

Reference specimens and playbooks worth studying when matching, reviewing or generating decks.

Browse by category

13
same bodies your agent reads
how this gets used

Three things your AI does once the skill is loaded.

  • 01 Picks the arc.

    Reads concepts.arcs live, suggests the arc + 5–7 beats that fits your thesis.

  • 02 Lints your draft.

    Walks every slide through the canon checklists, names the rule each weak action title violates.

  • 03 Cites real decks.

    Pulls observed slides from 309k indexed examples — not made-up references.

Agent entry points

24
4 prompts · 24 tools · live
  • search_storytelling_corpus
    Search the Storytelling corpus

    Search the unified Storytelling skill corpus: method, canon, craft, examples and applied consulting/contrarian resources. The domain filter is a legacy source-family filter, not the public resource tree.

    markdown
  • get_storytelling_resource
    Get a Storytelling corpus resource

    Return the full markdown for one Storytelling resource. Prefer unified URIs like `storytelling://method/agents.md`, `storytelling://canon/story-arcs.md` or `storytelling://applications/forms/activist-deck.md`; legacy ids like `storymakers/meta/agents` still work.

    markdown
  • list_storytelling_corpus
    List the Storytelling corpus

    List logical Storytelling skill areas/categories/resources. `domain` is kept only as a legacy source-family filter.

    markdown
  • get_storymakers_method_pack
    Get the Storymakers method pack

    Return curated Storymakers method markdown: overview, 10-step process, Creative Trio agents, checklists, story arcs, loop examples, examples, textures or all. This is the MCP-backed version of the Claude Storymakers skill.

    markdown
  • list_storymakers_canon_filters
    List Storymakers canon filters

    Presearch the available Storymakers request lenses before asking for canon or observed slide inventory. Document kind is the primary category lens; source/source_type is preserved as producer provenance/backcompat.

    live db
  • get_storymakers_canon
    Get the Storymakers canon

    Return the converged Storymakers canon: Postgres concepts.* is the source of truth for arcs, loops and tools, and MCP markdown resources are returned as companion bodies/examples. Call list_storymakers_canon_filters first when you need valid document kinds, layers, agents, slide types or component lenses.

    db + md
  • documents_count_by_kind
    Count documents by kind

    Return the number of documents in the storytelling corpus (Postgres-backed) grouped by document kind. Documents with no classification appear under "unclassified".

    live db
  • get_deck_playbook
    Get a deck playbook

    Return the structured PlaybookDeck for one corpus document — slides, arc beats, loops, action titles, slide functions. Identifier accepts UUID or slug. Output is a compact prompt-friendly summary by default; pass format="json" for the full structure.

    live db
  • search_slides
    Search slides

    Faceted slice over corpus.page_metadata. `kind` selects the lens (slide_type, slide_function, component, chart, metric, tool, framework, arc, beat, loop, all) and `value` filters that lens. Document-level filters (kinds, sourceTypes, orientations) further narrow the scope. Returns up to `pageSize` rows (max 24).

    live db
  • get_slide
    Get one slide detail

    Return the full SlideDetail for one (docId, pageNumber) — components, metrics, framework/tool/arc-beat/loop matches. Use the `docId` from search_slides results.

    live db
  • search_slides_semantic
    Search slides by meaning

    Meaning-first slide retrieval for deck-building agents. Describe the slide you need ("waterfall showing cost reduction across business units", "timeline of regulatory milestones with a call to act now") and get real corpus slides ranked by embedding similarity (cosine, text-embedding-3-small). Optional `document_kind` narrows to one kind (e.g. consulting-deck, pitchdeck, activist-deck); `entity_type: "deck"` searches whole decks instead of single slides. Follow up with get_slide({ docId, pageNumber }) or get_deck_playbook({ identifier }) for full detail.

    markdown
  • get_exemplars
    Get exemplar slides

    Return the N best real corpus slides for one canon lens: a tool (`tool_slug`), a slide type (`slide_type_slug`) or an arc beat (`beat_slug`). Pass exactly one of the three. Exemplars are ranked by match confidence and diversified (max 2 slides per document); each carries a signed image URL you can open as a multimodal input. Optional `document_kind` narrows to one deck kind (e.g. consulting-deck).

    markdown
  • get_narrative_priors
    Narrative priors from the corpus

    Aggregated narrative statistics for a slice of the enriched corpus (~10k docs): arc distribution, most common beat sequence, loop usage with typical open/close pages, SCQA completeness, example big ideas, audience×intent cross-tab. Pure SQL, no LLM. Filter by document_kind (e.g. consulting-deck, pitchdeck, activist-deck), audience (e.g. investors, executives), intent (e.g. persuade-decision, raise-capital) and/or author_name substring — at least one filter is required.

    markdown
  • get_layout_priors
    Layout priors for a slide type

    Where components sit on slides of a given type, aggregated from the corpus: per component kind, the share of slides that carry it, the median bbox (x,y,w,h normalized 0–1) with p25–p75 spread, and a verbal reading ("title: top band 5–12% of height, full width"). Filter by slide_type_slug (required, e.g. kpi_overview, executive_summary, section_divider), optionally document_kind and component_kind. Pure SQL over a bounded sample, no LLM.

    markdown
  • pressure_test_deck
    Pressure-test a draft deck

    Audit a draft deck against corpus priors — deterministic, no LLM. Four checks: title spine (all-caps, repeated openings, outlier lengths, stat stacking), arc coverage (deck vs the modal beat sequence of the document_kind, flagging missing beats), proportions (divider/evidence/assertion shares vs the kind median), and size (slide count vs p25–p75). Pass the deck as [{page, title, slide_type?, kind_hint?}] plus document_kind (e.g. consulting-deck) and optional audience/intent to narrow the prior.

    markdown
  • titles_examples
    Title examples by species

    Fetch anonymized gold or flagged-bad examples for one of the 10 title species. Examples come from the 230k+ enriched corpus and are filtered against the species-specific gold criterion.

    markdown
  • titles_anti_patterns
    Title anti-patterns

    Pedagogical lookup of named title anti-patterns: definition, severity, and the canonical fix. Pass a slug for a single entry, omit it to list all 14.

    markdown
  • titles_species_card
    Title species card

    Render one species ficha with live corpus data — same content as the `storytelling://copywriting/titles/species/<slug>` resource, exposed as a tool for callers that prefer the tools/call surface.

    markdown
  • titles_spine_check
    Title spine check

    Audit a sequence of titles (in deck order) against deterministic wiring rules: all-caps share, first-word repetition, word-count outliers, stat-fact stacking, open/close echo. Returns a list of findings keyed by rule.

    markdown
  • titles_grade
    Grade a draft title

    Diagnose a single draft title against the species taxonomy, the three quality gates (headline / forward / 8-second), the 14 anti-patterns, and the pair pattern. Backed by `claude -p` (Opus by default; ~5–25s per call).

    markdown
  • titles_rewrite
    Rewrite a draft title

    Propose up to 3 candidate rewrites for a draft title. Each candidate must pass the three quality gates and be defensible by the evidence summary (if provided). The model declines when the evidence is too thin, returning a blocked_reason. Backed by `claude -p` (Opus default; ~10–30s per call).

    markdown
  • search_patterns
    Search contrarian applications (deprecated)

    ⚠ Deprecated alias — will be removed 2026-07-01. Use search_storytelling_corpus({ domain: "contrarian" }) instead. Original behavior: BM25 search over the contrarian/activist application subset.

    markdown
  • get_pattern
    Get contrarian application markdown (deprecated)

    ⚠ Deprecated alias — will be removed 2026-07-01. Use get_storytelling_resource({ id: "contrarian/<category>/<slug>" }) instead. Original behavior: read one contrarian/activist application markdown body.

    markdown
  • list_categories
    List contrarian application categories (deprecated)

    ⚠ Deprecated alias — will be removed 2026-07-01. Use list_storytelling_corpus({ domain: "contrarian" }) instead. Original behavior: list categories within the contrarian/activist application subset.

    markdown
stop browsing — start asking

You've seen what's inside. Wire it into your AI.

Reading the resources is one path. The faster path: install the MCP once, and let Claude, Cursor or Codex pull the right resource for whatever you're working on. One install, every IDE.