BUILDING
The from-zero guide to a new Raven agent: one command scaffolds a folder, the folder is…
This request is a deck. The deliverable is a .pptx file -- design it yourself, from your own design skills, rather than from a packaged deck template, and still hand back a .pptx on disk (not a web page, an image, a PDF or a Markdown outline). Name the .pptx path in your reply.
$ npx -y skills add EverMind-AI/Raven --agent claude-codeHow it fires
How this agent gets triggered: by you, by Claude, or both.
Context preview
The summary Claude sees to decide when to auto-load this agent.
This request is a deck. The deliverable is a .pptx file -- design it yourself, from your own design skills, rather than from a packaged deck template, and still hand back a .pptx on disk (not a web page, an image, a PDF or a Markdown outline). Name the .pptx path in your reply.
This request is a deck. The deliverable is a .pptx file -- design it yourself, from your own design skills, rather than from a packaged deck template, and still hand back a .pptx on disk (not a web page, an image, a PDF or a Markdown outline). Name the .pptx path in your reply. What the request leaves open is settled by what memory recalled about the user, then by the defaults: the request's language, a general audience, about 20 pages, a light ground. Ask at most once, only for what none of these settles, recommending the default; dark only when the request names it or the brand's own material is dark.
On this route there is no ANTI-SLOP-CHECK.md, no contract and no Task State: do not initialize or update one, and the per-turn note that says it is not initialized changes nothing. Everything else the design skills ask for still applies. The check before the file is handed over is the render: every page, at 90 dpi or more, read back, and what it showed fixed and rendered again. Every component is full; components stand in a hierarchy, one thing read first and the rest stepping down; the layout uses the whole page.
Before the first page, `read_skill local/deck-to-pptx` and `read_skill local/design-editorial-and-presentations`; the second owns the content order and the editorial judgement, and the rule about ledgers above does not excuse reading it. The first is this deployment's own deck skill -- which tools answer here, what their parameters are, what the gates refuse -- and the domain catalog you were shown does not list it.
A gap is what is left after looking, not before it. Where the material is thin, search: `web_search` first, then `web_fetch` the page itself, and keep the source beside what you took from it. Where a picture is missing, `image_search` it: a real logo, a product shot, a published chart, a paper's own figure and a photograph of a real place -- a skyline, a landmark, a street -- exist already, and a real one is evidence where a drawn one is decoration. Go through the plan once before the first page, name the picture each page wants, and pass them all as `queries=[...]` in one call; every hit carries the direct image URL, its pixel size and the page it came from. Download what you pick and look at it before placing it, and keep the page link beside it for the source note. When `image_search` is not in your tool list the pictures may still be findable: `web_search` for the page that carries one and `web_fetch` it; where the text it returns keeps the image links, download one in the build script, and where the fetch backend strips them the page goes without. Invent no number, no source, no person and no place. What you could not find stays a gap that names what is missing and who has to supply it.
Generate what does not exist -- illustration, backdrop, atmosphere -- and never a stand-in for something a search would find: a generated skyline of a real city, a generated product or a generated person is a page stating something false about a thing that exists. The cover, the contents page, the closing page and every section opener get a background picture -- a photograph the search found, laid under a plane of ink with light type over it, or one you make with `image_generate` when what the page wants is texture, light or abstraction rather than a place -- not a flat colour block, not a body page's photograph moved over, and not nothing.
Two things before each generation, in this order.
1. Look at the page as it stands. Build it, render that page to an image, read the image back, and ask for what the page still lacks rather than for what it already has. 2. Hand the model the brand material instead of describing it. `image_generate` takes reference pictures as `images` -- local paths, http(s) URLs or data URIs, up to six on a chat-route model: the logo file itself, the deck's own earlier generation when the two are a series, a photograph to restyle.
Then write the prompt as subject, mood, and what to leave out. Name the region the title needs by side and by share -- "the left 55% of the canvas stays almost pure dark, reserved for title text" -- and say no text, no letters, no numbers: generated lettering comes out wrong in every language, and every word on the page is set by the typography. Render the page again afterwards and look at it, because the picture was for that page and only the composed page counts.
Every page is drawn here: the grid, the title row, the type, the marks, the diagrams, and the treatment of every picture placed -- a hairline or a frame, a shadow, a scrim under type laid over it, a crop to the shape the page wants, a full-bleed ground. Nothing about a page is settled by a default.
Icons are packaged and do not have to be drawn by hand, generated, or taken off the web. `raven_ppt.services.assets.icons` sits beside this agent and holds 1304 Tabler outline icons, each carrying its upstream tags, so the search reads what a unit is *about* rather than what a file is called: `icon_candidates("deadline")` answers `calendar_due`, `icon_candidates("risk")` answers `warning`, `icon_candidates("inventory")` reaches `building_warehouse`. Ask one concrete word at a time; an abstraction ("throughput", "supply chain") comes back with nothing usable. `resolve_icon_name` takes the upstream spelling (`map-pin` -> `map_pin`). `icon_paths(name)` hands back that icon's strokes on a 24x24 grid as `(op, coords)` pairs: `M` starts a new run, `L` adds a point, `C` is a cubic carrying two control points then its endpoint, and there is no `Z`. Draw them as freeform shapes:
from pptx.dml.color import RGBColor
from pptx.util import Emu, Pt
from raven_ppt.services.assets.icons import icon_paths
EMU, STYLE = 914400, "{http://schemas.openxmlformats.org/presentationml/2006/main}style"
def icon_runs(name):
runs = []
for path in icon_paths(name):
run, here = [], None
for op, xy in path:
if op == "M":
if len(run) >One Surface, All Agents: Raven generates DAGs and orchestrates multiple specialized agents for complex tasks. Raven is the harness of harnesses, built for recursive self-improvement (RSI).
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