--- name: Coin Hunter description: 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: - ` meme coin trending` - ` meme coin watchlist` - `new meme coin listed` - ` market cap liquidity` - ` holders tokenomics` - ` 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 ` 2. optionally run `python3 scripts/market_probe.py bybit-klines --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 ` 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
` 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.