Top Tweets for #Ringdom
Good article on harnessing your agent with bootloaders. I do harness every harness with my own harness. Then I make sure Agent does not forget about the overall project harness, when building for #ringdom:
how did we make deepseek outperform opus 4.7?
i've been thinking about why "open model bad at tool calling" is almost always a harness problem, not a model problem.
context: spent the two days looking at billions of tokens in @CommandCodeAI (tb open source ai cli) using deepseek. I ended up writing a tool-input repair layer. the trigger was watching deepseek-flash fail on the simplest /review run, every shellCommand and readFile call bouncing back with a raw zod issues blob, the model unable to recover because the error wasn't in a form it could read. by the end deepseek v4 pro was beating opus 4.7 6/10 times on our internal evals.
a few things i learned that feel general:
1/ the failure modes aren't random they're a small finite compositional set.
across deepseek-flash, deepseek v4 pro, glm, qwen, the same four mistakes repeat almost exactly:
- sending `null` for an optional field instead of omitting it
- emitting `["a","b"]` as a json *string* instead of an actual array
- wrapping a single arg in `{}` where the schema expected an array (an "empty placeholder")
- passing a bare string where an array was expected (`"foo"` instead of `["foo"]`)
four repairs, ~30-100 lines each, ordered carefully (json-array-parse must run before bare-string-wrap or `'["a","b"]'` becomes `['["a","b"]']`). that is the whole catalogue. when i hear "this open source model can't do tool calls" i now assume one of those four, and so far that's been right ~90% of the time.
2/ the funniest failure mode is also the most revealing.
deepseek-flash, when asked to edit or write a file, sometimes emits the path as a *markdown auto-link*:
filePath: "/Users/x/proj/[notes.md](http://notes. md)"
our writeFile tool obediently trued creating files literally named `[notes.md](http://notes .md)` until we caught it. this is not a hallucination. it's the post-training chat distribution leaking through the tool boundary the model has been rewarded for auto-linking in conversational output, and is applying that prior in a context where it makes no sense. the fix is two regex lines that unwrap only the degenerate case where link text equals url-without-protocol real markdown like `[click](https://x .com)` passes through untouched.
this is also conditioning of their own tools during RL which were different from all other tools we write and ofc can't predict.
"tool confusion" is a more useful frame than "capability gap." the model knows how to format a path. it just hasn't been told clearly enough that this path is going to fopen, not into a chat bubble. so we encode that hint at the schema level `pathString()` instead of `z.string()` and the leak is plugged for every path field at once.
3/ the design choice that mattered was inverting preprocess-then-validate to validate-then-repair.
my first attempt was the obvious one: a preprocessing pass that normalized inputs (strip nulls, parse stringified arrays, etc.) before zod ever saw them. it broke immediately, writeFile content that *happened* to be json-shaped got rewritten before it hit disk. silent corruption, easy to miss in a smoke test.
then i made it less greedy
- parse the input as-is. if it succeeds, ship it. valid inputs are never touched.
- on failure, walk the validator's own issue list. for each issue path, try the four repairs in order until one applies.
- parse again. on success, log `tool_input_repaired:${toolName}`. on failure, log `tool_input_invalid:${toolName}` and return a model-readable retry message.
the structural insight here is: when you preprocess, you encode a prior about what's broken. when you let the validator complain first, the schema is the prior, and you only spend repair budget at the exact paths the schema actually disagreed at. the validator is doing the work of localizing the bug for you. it's the same shape as cheap-then-careful everywhere else try the fast path, fall back on evidence.
(this also gives you per-tool telemetry for free. you can watch repair rates per (model, tool) and notice when a model regresses on a specific contract before users do.)
4/ shape invariants and relational invariants need different fixes.
the four repairs above all handle shape problems wrong type, missing key, wrong container. but read_file had a *relational* invariant: "if you provide offset, you must also provide limit, and vice versa." deepseek kept calling `readFile({ absolutePath, limit: 30 })` and getting an `ERROR:` back. you can't fix this with input repair, because each field is independently valid the bug is in the relationship between them.
so i taught the function the model's intent instead. `limit` alone โ `offset = 0`. `offset` alone โ `limit = 2000` (matches common read tool ops default). then surfaced the decision back to the model in the result:
"Note: limit was not provided; defaulted to 2000 lines. To read more or fewer lines, retry with both offset and limit."
no `Error:` prefix, so the tui doesn't paint it red. the model sees what we picked and can self-correct on the next turn if our guess was wrong. transparency over silent magic wins big.
repair where you can. extend semantics where you can't. surface the choice either way.
zoom out:
a lot of what looks like model capability is actually contract design. a strict schema is a choice with a cost it filters out noise, but it also filters out recoverable noise from any model that hasn't memorized the exact json contract you happened to pick. the largest commercial models eat that cost invisibly and are linient on tool calling because they've seen enough of every contract during pretraining; open models pay it loudly and get dismissed for it.
the harness is where you mediate between distributions. four small repairs (i'm sure more to follow as we have three more merging today), two regex lines for auto-links, one relational default, one prefix change. the model didn't change. the contract got more forgiving in exactly the places it needed to be.
deepseek v4 pro now beats opus 4.7 6/10 times on our internal evals.
imo "skill issue" applies to the harness more often than the model.
Together with @cursor_ai IDE, @AnthropicAI Claude Opus for excellent planning, GPT-5.5 and Composer 2.5 for flawless execution, together we are building something incredible and never seen before. #legiox #reggie #ringdom #sonoratek #radiusaz
God is Good. Super amazing.
I won Best Thrilling Hook on Stary Escaping Contest ๐ญ๐ญ thank you for giving me this chance @StaryWriting
"WHEN DEATH SKIPPED A SOUL"
link: https://t.co/ZyUfYheCaP
#novel #story #dreame #ringdom #writer #author #starywriting
https://t.co/JcvV92ZWar
The magical world of the elven Realm.
The Throne of Arbediin (18+ Mature Content)
Already Completed & Free to Read. Exclusive on Dreame & Ringdom ๐
#reverseharem
#Dreamers #ringdom #starynovel #cuteboys #fantasy #dreame #storypromotion #onlinenovel
"Money and apologies don't mean much to the Toymaker."
The Watcher reconnects with someone from his past...
https://t.co/6YkUGPJkAf
#Ringdom #Webnovel #WritingCommunity
He's here!
Click here ๐ https://t.co/vAL3cyMyIj and search for ๐to begin reading.
#ringdom #story #bookrecommendations #fantasy? #reading
"Soul Lovers" Still ongoing. Chapter 31 - Hunters' Invasion. Come read and Enjoy the moments!!
#dreame #ringdom #Grace #wednesday #WritingCommunity #YoungAdult #books #poetry #series #amwriting #writers #readers #writers #soullovers
Sneak peak of Soul Lovers on Dreame.
#dreame #ad #writers #writerxfictions2020 #writerslift #writing #WritingCommunity #readers #readerscommunity #ReadersFavorite #SoulLover #soulstories #Soulmates #SOULMATE #grace #ringdom #starywriting #manga #series #decisions #support
๐๐๐Click here to get Ringdom: https://t.co/0MJiC6B2q5, and search the book title Wolf Knight to read more!
#ringdom #story #bookrecommendations #fantasy #reading
๐๐๐Click here to get Ringdom: https://t.co/0MJiC6B2q5, and search the book title Chronicles of the Wolf I: Of Wolves and Spiders to read more!
#ringdom #story #bookrecommendations #fantasy #reading
๐๐๐Click here to get Ringdom: https://t.co/0MJiC6B2q5, and search the book title I Want To Live to read more!
#ringdom #story #bookrecommendations #fantasy #reading
๐๐๐Click here to get Ringdom: https://t.co/0MJiC6B2q5, and search the book title GENESYS to read more!
#ringdom #story #bookrecommendations #fantasy #reading
Might be a bit early still. Does anyone know the Vanguard Undercard for the Sheamus RD? #WWESuperCard #RingDom #2020SoFar
Finished #RingDom and also got a tier pull. Single, but still a good pull imo. Not even bothering with heroic. It's nice to just have a female ss19 pro finally ๐คฃ๐ #WWESupercard
This is why I stopped playing this BS game. #WWESupercard has completely gone down the drain. I get this nonsense after every #RingDom match. Looks like I aint getting the event card. Good job @WWESuperCard !
This always f**king happens...so damn irritating!
#WWESuperCard #ringdom #ringdomination @WWE @SUPERZOMGBBQ @WWESuperCard
@Shubham_7778 @KhajuriaManu Who added
#Sanku #Kargil with a #Shia majority to #Zanskar Assembly and removrd #Ringdom in Zanskar a Buddhist dominated village??
Who is Effectively depriving Buddhists Zanskaris their say. @JKNC_
@jkpdp @INCIndia or @BJP4India @jandkgovernor ??
#JKMinorities
Last Seen Hashtags on Sotwe
uncut #chubby
Seen from Netherlands
nolimits filter:videos
Seen from United States
incesto tรญa y sobrino
Seen from United States
ometv
Seen from Brazil
momsonn(**********) filter:videos
Seen from United States
baddie latina
Seen from United States
norma zzz
Seen from Korea
omegle((*)) filter:native_video
Seen from Brazil
momsonn
Seen from United States
Most Popular Users
Elon Musk 
@elonmusk
241.5M followers
Barack Obama
@barackobama
119M followers
Cristiano Ronaldo
@cristiano
114M followers
Donald J. Trump
@realdonaldtrump
111.8M followers
Narendra Modi
@narendramodi
107.2M followers
Rihanna
@rihanna
98.7M followers
NASA
@nasa
92.4M followers
Justin Bieber
@justinbieber
91.8M followers
KATY PERRY
@katyperry
89.8M followers
Taylor Swift
@taylorswift13
83.7M followers
Lady Gaga
@ladygaga
75.2M followers
Virat Kohli
@imvkohli
73M followers
Kim Kardashian
@kimkardashian
70.8M followers
YouTube
@youtube
68.8M followers
Neymar Jr
@neymarjr
66M followers
Bill Gates
@billgates
65M followers
Selena Gomez
@selenagomez
62.9M followers
The Ellen Show
@theellenshow
62.3M followers
CNN
@cnn
61.8M followers
X
@x
60.7M followers