Walrus research
Research Walrus storage usage patterns and product opportunities. Use when the user wants Walrus research, market gaps, or storage opportunities.From its SKILL.md
npx -y skills add pivyme/suiperpower --skill walrus-researchAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 12 stars12 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
6.7 KB, ~1.6k tokens by cl100k_base, as published. Nobody here has run it
Preamble (run first)
# Suiperpower telemetry. Routes through the CLI so projects.json + Convex stay in sync.
# Silent on failure so the skill never blocks. Opt out: SUIPERPOWER_TELEMETRY=off.
#
# AGENT NOTE: when this skill finishes, run the matching completion command:
# suiperpower track walrus-research idea completed
# Or use "failed" / "aborted" if it ended that way.
command -v suiperpower >/dev/null 2>&1 && suiperpower track walrus-research idea started >/dev/null 2>&1 &
true
If TEL_PROMPTED is no, before doing real work, ask the user:
Help suiperpower get better. We track which skills get used and how long they take. No code, no file paths, no PII. Change anytime in
~/.suiperpower/config.json.A) Sure, anonymous B) No thanks
Write the answer to ~/.suiperpower/config.json telemetryTier field and create ~/.suiperpower/.telemetry-prompted. Then continue.
What this skill does
Surveys current Walrus storage usage and turns it into a list of product opportunities. Walks four categories: media products, archive products, identity / verifiable storage, and developer tooling. Output is a ranked candidate list grounded in observed usage patterns and gaps in tooling, not generic "decentralized storage" framings.
The Walrus value proposition is durable, available, content-addressed blob storage with payment in WAL. The gaps are usually at the integration layer (apps, tooling, gateways), not the protocol layer.
When to use it
- The user wants to build on Walrus but is exploring use cases.
- The user is mid-validation of a Walrus-adjacent idea and wants traction signals.
- The user is sponsor-track-aligned (Sui Overflow Walrus track) and needs a load-bearing integration angle.
When NOT to use it
- The user wants to build a Walrus integration with a chosen idea, route to
walrus-storage. - The user wants general Sui idea search, route to
find-next-sui-idea. - The user wants DeepBook research, route to
deepbook-research.
If you activated this and the user actually wants something else, consult skills/SKILL_ROUTER.md and hand off.
Inputs
- The user's interest in Walrus (curious, picking an idea, validating).
- Optional: a content type the user has in mind (images, video, datasets, archives).
- Optional: the user's chain experience.
Outputs
A research block written to .suiperpower/idea-context.md (or a new .suiperpower/research-walrus-<timestamp>.md if no idea is chosen yet):
## Walrus research, <timestamp>
### Usage patterns observed
- <pattern>: <evidence>
- ...
### Underserved use cases
1. <use case>: <evidence>, <product idea this enables>
2. ...
### Gaps in tooling
- <gap>: <evidence>, <product idea this enables>
### Risks and constraints
- <risk>: <mitigation>
### Citations
- <Walrus docs link, observability dashboard, sponsor RFP, etc>
Workflow
-
Confirm scope
- Open-ended Walrus research, or focused on a specific content type?
-
Scan Walrus usage signals
- Read the official Walrus dashboard (suiscan.xyz/mainnet/Walrus or equivalent) for active publishers and aggregators.
- Survey known consumer apps integrating Walrus (NFT marketplaces using Walrus for media, dapps using it for static assets, etc.).
- Note volume signals (blobs published per day, total size, payment activity in WAL).
-
Walk the four categories
- Media products: NFT marketplaces, content-creator platforms, social media, image / video sharing. Where do existing apps fall short on storage durability, hosting cost, or content-addressing?
- Archive products: legal documents, scientific datasets, government records, backups. The "permanent storage" angle. Who needs verifiable, long-lived storage today?
- Identity / verifiable storage: user-controlled storage of identity documents, credentials, signed artifacts. zkLogin + Walrus + capability gates is a Sui-native composition.
- Developer tooling: Walrus gateways, indexing tools, content-addressing helpers, Walrus-as-a-CDN, frameworks for app developers.
-
Identify underserved use cases
- For each category, name at least one use case where current solutions are unsatisfying (web2 risky, IPFS unreliable, S3 expensive at scale).
- Tie each use case to a specific user (not "users", not "developers", but a named persona).
-
Identify tooling gaps
- Is there a public Walrus gateway with a CDN-grade SLA?
- Is there an indexing layer for blob discovery?
- Is there a framework for "Walrus + Sui Object" composability?
- Is there a billing / metering tool for app developers managing WAL spend?
-
Risks and constraints
- Walrus pricing in WAL: is the WAL/USD curve at a level that makes the use case unit-economic-positive?
- Latency and read patterns: Walrus is for blob storage, not realtime database. Use cases that need sub-100ms reads at scale should be flagged.
- Sponsor risk: Walrus is sponsor-backed; map out the sponsor relationship if the candidate's business model depends on Walrus stability.
-
Citations
- Every claim links to docs, a dashboard, an existing project, or a community post.
- Refuse claims without citations.
-
Writeback
- Append to the chosen output file.
Quality gate (anti-slop)
Before reporting done:
- Is each use case tied to a named persona, not "users"?
- Are tooling gaps cited with evidence (or explicit "no public solution found, last checked <date>")?
- Did the analysis include unit-economic considerations (WAL spend per user / blob)?
- Did the analysis avoid "decentralized storage is the future" framing without specifics?
- Did the writeback happen?
If any answer is no, the skill keeps working.
References
On-demand references (load when relevant to the user's question):
references/walrus-categories.md: Four-category decomposition with category-specific questions.references/walrus-unit-economics.md: How to think about WAL spend, gateway cost, pricing.
Knowledge docs:
skills/data/sui-knowledge/sponsor-docs/walrus.md: Walrus integration knowledge doc.skills/data/sui-knowledge/04-protocols-and-sdks.md: SDK and integration overview.
Use in your agent
- Claude Code:
claude "/suiper:walrus-research <your message>" - Codex:
codex "/walrus-research <your message>" - Grok Build: run
grok, then/walrus-research <your message>in the session - Cursor: paste a chat message that includes a phrase like "Walrus research", or load
~/.cursor/rules/walrus-research.mdcand reference it.
If you activated this and the user actually wants something else, consult skills/SKILL_ROUTER.md and hand off.
What ships with it: 3 files
7.4 KB alongside SKILL.md
agents/
- openai.yaml442 B
references/
- walrus-categories.md3.6 KB
- walrus-unit-economics.md3.4 KB