Files
coinhunter/SKILL.md
Tacit Lab 73a3cb6952 refactor: change data directory from .coin-hunter to .coinhunter
- Update SKILL.md references to use ~/.coinhunter/
- Update user-data-layout.md with new directory paths
- Update init_user_state.py ROOT path
- Unify naming convention with .stockbuddy style
2026-04-16 03:03:25 +08:00

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Coin Hunter Hunt, triage, and compare speculative crypto coins — especially meme coins, 妖币-style runners, fake-hype pumps, and possible rug/scam setups. Use when a user wants to actively search for coins with breakout potential, rank a shortlist, ask whether a coin still has "妖性", or check whether a token looks late, fragile, manipulated, or likely to be a scam.

Coin Hunter

Overview

Use this skill to help a user search for and judge high-volatility crypto setups without pretending certainty.

Default buckets:

  • candidate runner — has ingredients for further speculative expansion
  • watch-only / incomplete — interesting, but not clean enough yet
  • late / overheated — may still move, but entry quality is already poor
  • avoid / scam-risk — liquidity, distribution, credibility, or structure is too weak

Frame the work as speculative pattern recognition, not investment advice.

Core rule

Judge a coin by attention + liquidity + distribution + timing first. Narrative matters, but only when it can attract and hold money.

A technically weak project can still become a runner. A sophisticated-looking project can still be dead money.

Supported request types

Use this skill for four common modes:

  • single-coin triage — "look at this coin"
  • active discovery — "find me coins that could become 妖币"
  • shortlist ranking — "which of these 5 is most interesting"
  • scam / rug check — "is this coin just fake hype"

If the request is broad, ask at most one compact clarifying question. Prefer:

  • chain
  • theme / narrative
  • risk level
  • whether the user accepts microcaps or wants only reasonably tradable names

If no preference is given, default to: liquid speculative candidates, not ultra-illiquid microcaps.

Workflow

1. Identify the mode

Decide whether the user wants:

  • discovery
  • triage
  • comparison
  • scam-check

Then bias the workflow accordingly.

2. Choose the data path

Use structured market data first when available. Use web search to discover names and collect context, not as the only source of truth.

Preferred source order:

  • Bybit for real-time-ish price, 24h turnover, and tradability on a major venue
  • DexScreener for meme-coin pair discovery, DEX liquidity, and small-cap flow
  • Birdeye for Solana token activity and confirmation
  • CoinGecko for market-cap, rank, and metadata cross-check
  • web_search for discovery, narratives, and scam-discussion context

Private user state must live outside the skill directory under ~/.coinhunter/, not inside skills/coinhunter/. Read references/provider-playbook.md when choosing which source to trust first. Read references/user-data-layout.md when adding or updating personal accounts, positions, watchlists, or notes. Use scripts/market_probe.py for deterministic provider lookups. Use scripts/init_user_state.py to initialize the private user-data directory.

3. Discovery mode: build a candidate list

When the user wants active search rather than analysis of a known ticker, use public web sources to build a shortlist.

Look for evidence of:

  • rising attention
  • listing or venue expansion
  • narrative/theme alignment
  • market-cap and liquidity context
  • breakout discussion or unusual participation

Useful search patterns include:

  • <theme> meme coin trending
  • <chain> meme coin watchlist
  • new meme coin listed
  • <coin> market cap liquidity
  • <coin> holders tokenomics
  • <coin> rug risk

Do not trust a single source or a single viral thread. Build the list first, then vet the names.

Read references/search-workflow.md for the detailed discovery flow.

4. Triage mode: score the coin on six dimensions

Assess each coin qualitatively across these dimensions.

A. Narrative fit

Ask:

  • Is the story attached to a live theme?
  • Is the idea easy to repeat in one sentence?
  • Does the symbol / meme / framing have social spread potential?

Strong examples:

  • obvious meme identity
  • attached to a live chain or hot sector
  • easy cultural hook

Weak examples:

  • vague utility story
  • no memorable angle
  • cold or stale narrative

B. Attention acceleration

Ask:

  • Is visibility rising now?
  • Is the coin spreading beyond its original niche?
  • Are larger accounts, aggregators, or trading communities starting to notice it?

Treat acceleration as more important than absolute popularity.

C. Liquidity quality

Ask:

  • Can a normal user realistically enter and exit?
  • Is volume believable relative to market cap and attention?
  • Are spreads or venue quality obviously problematic?

If the user can probably buy but may not be able to exit cleanly, score this harshly.

D. Distribution / holder risk

Ask:

  • Is ownership too concentrated?
  • Are deployer or team wallets still dangerous?
  • Is there an obvious unlock or dump overhang?

Ugly distribution does not automatically kill a trade, but it makes the setup fragile.

E. Timing / chart state

Ask:

  • Is it emerging from a base or already vertical?
  • Has participation expanded recently?
  • Do pullbacks hold, or do they collapse?

Prefer:

  • fresh breakout from longer consolidation
  • early or mid-stage expansion
  • resilient retraces

Be cautious when:

  • it already went parabolic
  • volume fades after the first mania burst
  • price action is mostly wick-and-dump behavior

F. Rug / scam risk

Check for:

  • fake partnerships or fake listing claims
  • unverifiable team paired with aggressive promotion
  • suspicious contract / public warning signals
  • impossible tokenomics promises
  • unverified liquidity-lock claims
  • nothing but shill posts and no independent discussion

One severe scam signal can outweigh several bullish ones. Read references/scam-signals.md when the user specifically asks about rugs, scams, fake hype, manipulation, or exit-liquidity bait.

5. Classify the result

Use these buckets:

Candidate runner

Use when most are true:

  • narrative is live
  • attention is accelerating
  • liquidity is usable
  • timing is not obviously exhausted
  • no fatal scam / exit-risk signal is present

Watch-only / incomplete

Use when:

  • something is interesting, but evidence is incomplete
  • narrative is decent but timing is unclear
  • liquidity or distribution is acceptable but not clean
  • it deserves monitoring more than action

Late / overheated

Use when:

  • the move is already widely noticed
  • chart is extended or near blow-off behavior
  • upside may remain, but entry quality is poor
  • new buyers are at risk of becoming exit liquidity

Avoid / scam-risk

Use when:

  • liquidity quality is bad
  • exit risk is high
  • holder concentration is dangerous
  • legitimacy claims are weak or fake
  • the setup feels more fabricated than organic

Provider execution patterns

Known tradable coin

If the user gives a Bybit-listed ticker or asks for current price/tradability:

  1. run python3 scripts/market_probe.py bybit-ticker <SYMBOL>
  2. optionally run python3 scripts/market_probe.py bybit-klines <SYMBOL> --interval 60 --limit 10
  3. cross-check with CoinGecko when market-cap context matters

Meme / 妖币 discovery

If the user wants runners, meme coins, or small-cap candidates:

  1. use web_search to gather names
  2. run python3 scripts/market_probe.py dex-search <name> for the strongest candidates
  3. if Solana, run Birdeye when API access is configured
  4. use CoinGecko to verify market-cap and ranking
  5. only use Bybit if the coin is also on a major CEX

Birdeye requirement

market_probe.py birdeye-token <address> requires BIRDEYE_API_KEY in the environment. If it is not configured, say so briefly and continue with DexScreener + CoinGecko + web search.

Private portfolio state

If the user wants account, position, watchlist, or thesis tracking for coinhunter:

  1. initialize ~/.coinhunter/ with python3 scripts/init_user_state.py
  2. store private data only there
  3. never place personal holdings inside the skill folder
  4. treat the skill folder as logic only, and the user-data directory as state only

Output style

Default to compact, decision-first answers.

For a single coin, include:

  • Verdict
  • Radar score — use the 0-12 checklist when evidence is sufficient
  • Why it could run — 2-4 bullets
  • Why it could fail — 2-4 bullets
  • What confirms strength
  • What kills the thesis
  • Risk line — clearly state this is speculative, not investment advice

For multiple coins:

  1. rank the shortlist
  2. mark each as candidate runner / watch-only / late / avoid
  3. state the main attraction and main flaw for each

Prefer bullets, short sections, and hard judgments over long essays. Use references/output-templates.md when you want a reusable answer skeleton.

Practical heuristics

Often bullish for speculative expansion

  • the meme or story is instantly repeatable
  • attention is accelerating, not just present
  • volume expands with the move
  • pullbacks are bought
  • exchange accessibility improves
  • more mainstream crypto accounts begin to mention it

Often a sign it is late

  • everyone is already talking about it
  • the chart has been vertical for days
  • promotion is everywhere after the main move already happened
  • price keeps spiking while structure gets messier

Often a sign to avoid

  • no trustworthy liquidity information
  • suspicious ownership concentration
  • clearly manufactured chart behavior
  • incoherent or constantly shifting explanation
  • obviously botted or repetitive social activity

What not to do

  • Do not describe a coin as safe.
  • Do not confuse a polished whitepaper with breakout potential.
  • Do not imply expected returns.
  • Do not recommend leverage.
  • Do not ignore slippage and exit risk.
  • Do not push microcaps on beginners unless the user explicitly asks for extreme risk.

Optional deeper pass

If the user wants more depth, expand in this order:

  1. narrative and timing
  2. liquidity and market structure
  3. holder / tokenomics risk
  4. why it could become a runner
  5. why it probably will not
  6. watch triggers

References

Read references/provider-playbook.md for source selection and provider roles. Read references/user-data-layout.md for private state layout under ~/.coinhunter/. Read references/radar-checklist.md for a quick scoring framework. Read references/search-workflow.md for active discovery. Read references/output-templates.md for compact response structure. Read references/scam-signals.md for sharper scam / fake-hype judgment.