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"namespace:io.github.datmay-dot" matching MCP tools:

  • Search WhatDoTheyKnow's feed-based event index and return structured results. Call this to find FOI requests matching a query expression. Returns up to `limit` AtomEntry objects. Use the `link` field of each result as the next navigation step — extract the request slug and call the wdtk://requests/{slug} resource or get_request_feed_items for full detail. Example expressions: status:successful body:"Liverpool City Council" (variety:sent OR variety:response) status:successful
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  • Is macro with you or against you? Get the current regime (bull/bear/risk_on/risk_off/choppy), directional signal and confidence, and macro context (DXY, VIX, fear/greed) before entering a position. Data-only, no LLM latency. coverage disclosed per token. REST equivalent: POST /analyze/market (0.25 USDC). Args: token: Token symbol (BTC, ETH, SOL, XRP, ADA, DOGE, AVAX, LINK, BNB, ATOM, DOT, ARB, SUI, OP, LTC, AMP, ZEC) context: Optional historical context window ('7d' or '30d'). Adds percentile rankings.
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  • Full pre-trade diligence in one call. Gets all market and orderflow data, then makes a grounded judgment: BULLISH/BEARISH/NEUTRAL stance, ACCUMULATION/DISTRIBUTION signal, LOW/MODERATE/HIGH/CRITICAL risk level, and a verdict that cites actual data values — not vibes. Use when you want a single answer rather than assembling the pieces yourself. coverage disclosed per token. REST equivalent: POST /analyze/full (0.75 USDC). Args: token: Token symbol (BTC, ETH, SOL, XRP, ADA, DOGE, AVAX, LINK, BNB, ATOM, DOT, ARB, SUI, OP, LTC, AMP, ZEC) context: Optional context window ('7d' or '30d').
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  • What is the current price of Bitcoin, Ethereum, or any major crypto? Returns the latest USD price, 24-hour price change percentage, trading volume, and market cap. Updated every 15 minutes from CoinGecko and Binance. Supports 20 assets: BTC, ETH, SOL, BNB, XRP, ADA, AVAX, DOT, MATIC, LINK, UNI, ATOM, LTC, FIL, NEAR, APT, ARB, OP, INJ, SUI. Example: get_crypto_price('BTC')
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  • What's the market doing right now? Price, funding rate, CVD, whale activity, and liquidation pressure in one call — 16 fields, no LLM overhead. Feed directly into your own models or decision logic. orderflow coverage disclosed per token. REST equivalent: POST /data (0.20 USDC). Args: token: Token symbol (BTC, ETH, SOL, XRP, ADA, DOGE, AVAX, LINK, BNB, ATOM, DOT, ARB, SUI, OP, LTC, NEAR, TRX, BCH, SHIB, HBAR, TON, XLM, UNI, AAVE, AMP, ZEC)
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  • Create a new API test suite with test steps. Each step defines an HTTP request and assertions to validate the response. Steps can extract values from responses into variables for chaining requests. ═══════════════════════════════════════════════════════════════════ STEP 0 — read the canonical schema BEFORE drafting: ═══════════════════════════════════════════════════════════════════ If you've already called get_app_testing_context, the canonical step schema is in its response under the `step_schema` field — read it from there. Otherwise run `keploy test-suite-format` once before writing any suite JSON. The schema describes the MANDATORY rules below in detail plus the two-step prelude+POST skeleton you must follow. Authors who skip this and draft from training-data priors burn ~50s per validator rejection on iter 1. ═══════════════════════════════════════════════════════════════════ MANDATORY FOR EVERY STEP — the validator rejects on iter 1 if any of these are violated: ═══════════════════════════════════════════════════════════════════ R10 — every step MUST carry a captured "response": {status, body, headers} block. Hit the endpoint locally before authoring (curl) and paste the real response. Steps with no response block are rejected outright; four downstream rules (R4 / R11 / R15-R16 / R27) silently no-op until R10 is satisfied, so missing a response also hides every assertion / extract problem in that step. R9 — every POST / PUT / PATCH body MUST reference at least one {{var}} whose generator is declared on an EARLIER step's "extract" (typically a /health prelude as step 0). Without this, the second run collides on the first run's database state. App-level appLevelCustomVariables DO NOT qualify for R9 — the validator only credits step-level extracts. R2 — pre-request fields ("body", "url", "headers") CANNOT reference the CURRENT step's own "extract" outputs. Extract runs AFTER the response comes back; pre-request substitution sees nothing yet. Together R9 + R2 force the prelude pattern: declare generators on step 0, use them from step 1+. The STEP SHAPE example below shows the canonical two-step layout. R15 — every assertion's path / status / header MUST resolve against the AUTHORED response block. JSONPath uses gjson dot-array syntax: $.orders.0.id — NOT $.orders[0].id (the bracket form does not resolve in gjson; the assertion is rejected as "key not present in recorded body"). For status_code / header_* assertions, the values must match what's in response.status / response.headers verbatim — capture the real response via curl before authoring. R32 — every step-level extract key MUST NOT collide with the app's appLevelCustomVariables (enumerate them via get_app_testing_context or getApp before authoring). The runtime's variable lookup resolves app-level first, so a colliding key means the suite's function silently never runs. Suite-suffix when in doubt: userNonceForSuite, not genUserId. Don't invent a parallel generator with the same name as an existing app-level one. ═══════════════════════════════════════════════════════════════════ APP CONFIG FIRST — read the app before authoring: ═══════════════════════════════════════════════════════════════════ Before any other step, call getApp({app_id}) and read these fields: * appLevelCustomVariables — dynamic generators and static fixtures pre-configured by the dev, shared across every suite for this app. Common shapes: - genUserId, genProductName (JS functions returning fresh entropy per run, e.g. `alice_<rand1-10000>`) - staticUser (a fixed user the dev wants tests to use) - zeroQuantity, negativePrice, invalidUser (static fixtures for validation tests) PREFER these over inventing your own JS-function in `extract`. They're the dev's authoritative dynamic-input set — using them in POST/PUT/PATCH bodies via `{{varName}}` means each replay hits a fresh row, sidestepping duplicate-key errors. Inventing a parallel generator with the same intent risks name-collision rejection (see Name-collision check below). * auth — the auth shape suites must satisfy (header / cookie / oauth / none). * ignoreEndpoints, rateLimit, timeout — runtime knobs that shape what assertions can hold. If a relevant `gen*` already exists in appLevelCustomVariables, ALWAYS reference it via `{{name}}` rather than authoring a parallel one. The dev configured it for a reason. ═══════════════════════════════════════════════════════════════════ BEFORE CREATING — check for duplicates AND for existing recordings: ═══════════════════════════════════════════════════════════════════ A (app_id, branch_id) tuple holds at most one suite per scenario, AND if the dev has already captured the relevant traffic via `keploy record`, you should seed from that recording instead of curling the app fresh. Two bounded checks before create_test_suite: (1) Duplicate-suite check — call listTestSuites({app_id, branch_id, q: "<scenario-keyword>"}) where <scenario-keyword> is a substring of the name you're about to author (e.g. "checkout", "auth"). The server filters by name regex, so the response is bounded to relevant matches regardless of how many suites the app has. If you can't pick a keyword (the dev's intent is vague), call with page_size=20 and NO q, then scan the first page only — DON'T paginate further. Match by name (case-insensitive) AND by intent. If any existing suite covers the same scenario: - Same scenario, refresh wanted → call update_test_suite (preserves history) or delete_test_suite + create_test_suite (loses history). - Adjacent but distinct scenario (e.g. "checkout with discount" vs "checkout without discount") → create with a name that distinguishes them clearly. (2) Recording-reuse check — call listRecordings({app_id, limit: 10}) to fetch the 10 most recent `keploy record` sessions. Recordings cluster by scenario; the top 10 cover what's likely relevant — DON'T paginate the full history. For any recording whose name/timestamp suggests it covers the scenario you're authoring, call download_recording({app_id, test_set_id}) to pull its captured test cases (real request/response pairs from the live app). Seed your steps_json from those test cases — convert each one into a step (method/url/headers/body → request fields; recorded response → step's `response` field). This is more faithful than re-curling and saves the dev's time. If no recent recording covers the scenario, fall through to the normal validate-locally-before-inserting flow (curl each endpoint yourself). (3) Only after both checks → proceed with create_test_suite. Skipping (1) leaves the dev with two suites covering the same flow — confusing reports, double rerecord cost, and orphaned sandbox tests on whichever suite they stop using. Skipping (2) re-curls endpoints whose traffic the dev already captured. ═══════════════════════════════════════════════════════════════════ ONE SCENARIO PER SUITE — load-bearing constraint: ═══════════════════════════════════════════════════════════════════ A suite represents EXACTLY ONE user-facing scenario / use-case (e.g. "user registers and creates their first order", "admin promotes a user role", "checkout with discount applied"). Do NOT pack multiple unrelated scenarios into a single suite — every step in a suite shares state and ordering with every other step. Mixing scenarios breaks idempotency (cleanup for one scenario can wipe state another scenario assumed), makes failures harder to diagnose, and inflates rerecord cost. Tests for "auth + payments + cleanup" → THREE suites, not one. Related steps that share extracted vars and a state assumption belong in the same suite; unrelated flows don't. When in doubt: if you can't write a single sentence describing what the suite tests in user-facing terms, split it. ═══════════════════════════════════════════════════════════════════ IDEMPOTENCY CONTRACT — the load-bearing rule for every suite: ═══════════════════════════════════════════════════════════════════ Every suite MUST be replayable indefinitely without state drift. The same suite run twice in a row, or 100 times back-to-back, must produce the same per-step outcomes. Failing this makes the suite useless for sandbox replay (the captured mocks freeze a single point-in-time response, so any state-dependent step diverges on rerun). How to design for it: * Duplicate-key 500 on POST / PUT / PATCH replay ("duplicate key" / "already exists" / "unique constraint violated") is ALWAYS a SUITE design problem, NEVER an app problem. Fix order: (1) Reference an app-level `gen*` var via `{{name}}` in the body — works if one exists (you read appLevelCustomVariables in APP CONFIG FIRST). (2) If no fitting app-level generator, declare your own JS-function in a PRIOR step's `extract` (see PRELUDE PATTERN); reference it via `{{name}}` in the failing step's body. (3) Add a DELETE cleanup step earlier in the suite to clear the conflicting row. NEVER propose modifying app code (e.g. adding `ON CONFLICT` to the INSERT, retry loops, transactional wrappers). The app's dedup is correct; the suite is what's missing entropy. See DO NOT MODIFY APP SOURCE CODE below. * If a step CREATES a resource, a later step in the same suite MUST clean it up (DELETE the row, revert the state) — OR the create must be idempotent on the server side (PUT-by-key, upsert). A naked POST that always allocates a new ID will diverge on every replay. * If a step depends on a resource, EXTRACT its identity from a prior step's response into a `{{var}}` — never hard-code an ID that "happens to exist right now". Hard-coded IDs rot. * Reject "natural-language idempotency" reasoning ("the dev will reset the DB before each run"). The suite must work without external setup. If you can't guarantee it, you've packed two scenarios into one suite — split them. * Do not assume time-of-day, ordering relative to other suites, or random-but-stable values. Each suite is its own universe. * Pagination / list endpoints: extract the count or a known item, don't assert on absolute indices ("the third item is X") — index drifts as the dataset grows. * Auth tokens: pull from app-level custom variables or extract from a login step IN THE SUITE. Never inline a token that expires. If the dev's request implies non-idempotent behaviour (e.g. "create user, then test that creating the same user fails"), capture both states explicitly inside the suite — first step creates, second step asserts the conflict response, third step deletes — so the suite as a whole is still replayable. Don't push the cleanup outside the suite. A suite that fails idempotency is rejected at create_test_suite time by the dynamic validator (2 live runs check). When that fails, do NOT retry by tweaking syntax — restructure the scenario. ═══════════════════════════════════════════════════════════════════ DO NOT MODIFY APP SOURCE CODE during suite authoring: ═══════════════════════════════════════════════════════════════════ At create_test_suite time, your job is to author a suite that fits the app AS IT IS. You may patch the app's CONFIG (auth, appLevelCustomVariables, ignoreEndpoints, rateLimit) via updateApp({app_id, ...}) — those are runtime knobs the dev expects to tune. You may NOT modify the app's SOURCE CODE. If a step is failing because of how the app behaves (500s, contract mismatches, missing endpoints, validation errors), the response is ONE of: * Adjust the suite to match observed behavior (steps_json edits before insert). * Use an app-level dynamic var (see APP CONFIG FIRST) or a JS-function generator to avoid the failure (see IDEMPOTENCY CONTRACT's duplicate-key fix order). * Patch the app's CONFIG via updateApp if the cause is auth / vars / rate limit. * If the dev confirms the app is broken AND the suite is correct, ASK the dev to fix the app — do NOT propose code changes yourself during authoring. NEVER propose ON CONFLICT clauses, retry loops, transactional wrappers, or any code-level change to the dev's application as a way to make the suite work. The suite must accommodate the app, not the other way around. ═══════════════════════════════════════════════════════════════════ NEVER-MISS-THESE — the validator HARD-REJECTS suites missing any of these: ═══════════════════════════════════════════════════════════════════ 1. `response` on EVERY step — { status: <int>, headers: {…}, body: "<string>" }. Captured from a real curl against the dev's app. body MUST be a JSON-encoded STRING (the raw body bytes), NOT a parsed object. Wrap with json.dumps / JSON.stringify if your tool gave you a dict. 2. `extract` is the ONLY authoring slot — never `extract_variables`. `extract_variables` is a post-run runtime SNAPSHOT field; the extract_variables-input rejection rule hard-rejects it on input. If you read an existing suite via getTestSuite / get_app_testing_context / download_recording and see `extract_variables` populated there — IGNORE IT, that's the runtime's display state, not the suite's input. Always author with `extract`. 3. POST/PUT/PATCH bodies need a per-run dynamic `{{var}}` (mutating-step dynamism check). Declare a JS-function generator on a PRIOR step's `extract` (typically a /health prelude as step 0). The declare-and-use-same-step check forbids declaring-and-using on the same step. See PRELUDE PATTERN below. 4. JSONPath uses gjson dot-array syntax: `$.orders.0.user_id` — NOT `$.orders[0].user_id`. ═══════════════════════════════════════════════════════════════════ STEP SHAPE (steps_json is an ARRAY — copy this two-step skeleton verbatim, preserve the prelude pattern): [ { // Step 0: cheap read prelude. Its sole job is to declare JS-function generators that // later POST/PUT/PATCH bodies reference. Required by R9 (mutating bodies need a per-run // dynamic var) + R2 (same-step extract isn't usable in pre-request fields). If your // suite already has a natural read step (/health, /me, version), reuse it as the prelude. "name": "health prelude (declares generators)", "method": "GET", "url": "/health", "headers": { "Accept": "application/json" }, "extract": { "genUserId": "function genUserId(){return 'u_'+Date.now()+'_'+Math.random().toString(36).slice(2,8);}" }, "assert": [ { "type": "status_code", "expected": "200" }, { "type": "json_equal", "key": "$.status", "expected": "healthy" } ], "response": { "status": 200, "headers": { "Content-Type": "application/json" }, "body": "{\"status\":\"healthy\"}" } }, { // Step 1: the actual mutation. Body references {{genUserId}} from the PRIOR step's // extract — satisfies R9 (per-run dynamic var) and R2 (not same-step). This step's // own "extract" captures the SERVER's response value (JSONPath) so a later step can // chain to {{user_id}} — JSONPath captures on the same step ARE legal because they // resolve post-response and only matter for subsequent steps. "name": "create user", "method": "POST", "url": "/api/users", "headers": { "Content-Type": "application/json" }, "body": "{\"name\":\"{{genUserId}}\"}", "extract": { "user_id": "$.data.id" }, "assert": [ { "type": "status_code", "expected": "201" }, // assert a STATIC field of the response, not a dynamic one. R30 // forbids {{genUserId}} in assert.expected (the runtime would // re-evaluate the function at assertion time and the value // wouldn't match the body's earlier call). Pick something the // server always returns the same — here the literal "status" // field. To assert against the dynamic id the server minted, // capture it via extract (above) and reference {{user_id}} in // a LATER step's assertion or url, not this step's. { "type": "json_equal", "key": "$.status", "expected": "created" } ], "response": { "status": 201, "headers": { "Content-Type": "application/json" }, "body": "{\"data\":{\"id\":\"abc-123\",\"name\":\"u_1700000000_xyz\"},\"status\":\"created\"}" } } ] VALID assertion types (ONLY use these — anything else fails the step at runtime with "invalid assertion type"): * status_code — exact HTTP status match. {type, expected:"201"} * status_code_class — match by class 2xx/3xx/… {type, expected:"2xx"} * status_code_in — any of a set. DELETE STEPS ONLY (status_code_in-scope check). For POST/GET/PUT/PATCH this is rejected. If you reach for it to absorb a duplicate-key 500 on re-runs, the right fix is a JS-function {{var}} in the body (see `extract` rules below) so each run hits a fresh row and only 201 is ever returned. {type, expected:"200,201,204"} * header_equal — response header exact match. {type, key:"Content-Type", expected:"application/json"} * header_contains — header value substring. {type, key:"Location", expected:"/orders/"} * header_exists — header is present. {type, key:"X-Request-Id"} * header_matches — header regex. {type, key:"Etag", expected:"^W/\\\".+\\\"$"} * json_equal — response body JSON path exact match. {type, key:"$.order.status", expected:"created"} * json_contains — response body JSON path substring/partial. {type, key:"$.message", expected:"success"} * custom_functions — inline JS function: (request, response, variables, steps) => boolean. {type, expected:"function f(request,response){return response.status===201;}"} DO NOT use any assertion type not in the closed list above. The set is fixed at exactly 10 entries — there are no wildcards. These are types AIs commonly invent that DO NOT EXIST in keploy and will fail the assertion-type closed-list check: ✗ json_type — there is no type-of check; assert against the literal value via json_equal, or use custom_functions with a typeof predicate. ✗ json_path — paths are passed via the "key" field of json_equal / json_contains; there is no separate path-only type. ✗ json_schema — no schema validation; closest is custom_functions with an inline schema check. ✗ json_array_length — no length-only assertion; capture .length via extract, or use custom_functions. ✗ header_starts / header_ends — only header_equal, header_contains, header_exists, header_matches (regex) exist. ✗ status_in / status_range — the real names are status_code_in / status_code_class. ✗ body / body_equal — no body-level type; assert against parsed paths via json_equal / json_contains, or use custom_functions. Anything not literally in the bulleted list above will get rejected by the validator — don't extrapolate from prefixes. `expected` values must be STRINGS (put numbers like 201 in quotes). `expected_string` is auto-populated; you can omit it. VARIABLES — purpose-first: a suite is a SCENARIO CHAIN; variables carry continuity between steps. Step N creates or fetches a resource → extracts its identity into a named var → step N+M uses `{{var}}` to reference that identity. If you find yourself extracting a value that NO LATER STEP references, DROP the extract — it's noise that hides which fields actually drive the scenario. Mechanically: extract values from one step's response with `extract: {varname: "$.path"}` (JSONPath). Reference later with `{{varname}}` in headers, body, url, or assertion `expected` values. STEP IDS & TRACKING HEADERS are auto-injected — don't provide them. The server assigns a UUID per step and adds X-Keploy-Test-Step-ID / X-Keploy-Test-Suite-ID / Keploy-Test-Name so the sandbox runner can correlate responses to steps. VARIABLE RULES (the runner follows these exactly — see pkg/service/atg/customFeatures.go ResolveCustomVariables): * Syntax: {{name}} — regex matched: {{(\w+)}} (letters, digits, and underscore only; NO whitespace, hyphens, or dots inside the braces). Names like {{gen-user}} or {{gen.user}} will NOT be substituted — use {{gen_user}} instead. * Substitution happens in: url, body, headers values, AND assertion "expected" values (so an assertion expecting {{genUserId}} gets the SAME resolved value the body used). * Resolution sources (looked up in this order): 1. The step's own `extract` map (seeded into the vars pool at step entry — pkg/service/atg/core.go:3698). 2. Variables produced by EARLIER steps' `extract` maps (post-response JSONPath captures). 3. App-level custom variables (stored on the app record, shared across all suites). THE `extract` FIELD IS THE ONLY AUTHORING SLOT — use it for BOTH static values and JS-function generators. `extract_variables` IS NOT AN AUTHORING SLOT. It's a post-run runtime SNAPSHOT — the runner writes resolved {{var}} values there after each step executes so the UI can show what landed at runtime. **The validator now HARD-REJECTS any step with `extract_variables` populated (extract_variables-input rejection).** If you see `extract_variables` while reading an existing suite via getTestSuite / download_recording / get_app_testing_context, IGNORE IT — that's the runtime's display state, not the suite's input. To author the equivalent, put every entry into `extract` instead (same keys, same values: JSONPath strings stay JSONPath, JS-function strings stay JS). TWO SHAPES THE `extract` FIELD ACCEPTS — pick the right one: (a) JSONPath capture — `"order_id": "$.order.id"` Evaluated against the step's recorded response.body after the request returns. The captured value is staged into vars for LATER steps to reference via {{order_id}}. Use this when the value you need is in the server's response. (b) Inline JS-function generator — `"genUserId": "function genUserId(){ return 'alice_' + Date.now() + '_' + Math.random().toString(36).slice(2,8); }"` The value string must contain the keyword `function` — that is how the runner (core.go:4107 isInlineJs branch) distinguishes JS from a JSONPath. Signature: function <name>(steps) { ... return '<string>'; } returning a string. The `steps` arg is a map of prior-step {request,response} snapshots; ignore it if unused. Use this for inputs that must be unique per run (user_ids, timestamps, uuids) so the suite stays idempotent on re-runs against the same DB. Examples: {"genUserId": "function genUserId() { return 'alice_' + Date.now() + '_' + Math.random().toString(36).slice(2,8); }"} {"genTs": "function genTs() { return String(Date.now() * 1e6 + Math.floor(Math.random()*1e6)); }"} {"genOrderId": "function genOrderId(steps) { return 'ord-' + Math.random().toString(36).slice(2,10); }"} Put the JS-function entry on the FIRST step that needs it (often a health-check step whose own body doesn't reference the var — that's fine, the seed fires on step entry regardless). Later steps reference `{{genUserId}}` in body/url/headers/assertion-expected and see the same resolved value within one run, a fresh value on the next run. WHY THIS MATTERS (the mistake to avoid): if you pin a static user_id like "alice_1776638347063146000" into `extract` AND your validation curl ALREADY inserted that row, the very next record/sandbox replay run will fire the same POST body, the producer (with deterministic ids or unique-constraint indexes) will reject the duplicate with a 500, and every downstream $.order.* / $.shard.* assertion will hit <missing>. Fix: use a JS-function entry so every run gets a fresh user_id. VARIABLE CHAINING (JS-function generator on step 1, JSONPath capture for step-2 chaining): step 1: body: {"user_id":"alice_{{genUserId}}","product_name":"Keyboard_{{genUserId}}"} extract: { "genUserId": "function genUserId(){ return Date.now() + '_' + Math.random().toString(36).slice(2,8); }", "order_id": "$.order.id" } assertions: [ {type:"status_code", expected:"201"}, {type:"json_equal", key:"$.order.user_id", expected:"alice_{{genUserId}}"} -- SAME resolved value as the body used ] step 2: url: /api/orders/{{order_id}} -- resolves from step 1's JSONPath extract at run time assertions: [ {type:"json_equal", key:"$.id", expected:"{{order_id}}"} ] PRELUDE PATTERN — when MULTIPLE POST steps each need their OWN per-run dynamic var: A common mistake is to put the JS-function generator on the SAME step that uses it in the request body. The declare-and-use-same-step check rejects this — same-step `extract` is post-response, so its values aren't in scope when the request fires. Pattern that works: declare the generator on an EARLIER step's `extract` (typically a cheap /health GET as a "prelude"). The runner seeds extract values at STEP ENTRY, so a generator on step 0 is in scope from step 0 onwards — every later POST can reference it. step 0 — prelude (the extract entry is what matters; the step itself can be anything cheap): method: GET, url: /health extract: { "uniq": "function uniq(){ return 'p_'+Date.now()+'_'+Math.random().toString(36).slice(2,8); }" } assertions: [ {type:"status_code", expected:"200"} ] step 1, 2, 3 — POSTs that all reference {{uniq}}: method: POST, url: /api/orders body: '{"user_id":"alice","product_name":"{{uniq}}",...}' // (no `extract` needed — the generator is in scope from step 0) The prelude itself doesn't need to USE the var; declaring it is enough. This is the right shape for "create N orders with different unique keys" — without the prelude, you'd hit the declare-and-use-same-step check on every POST that tries to declare-and-use a generator on the same step. VALIDATE-LOCALLY-BEFORE-INSERTING (CRITICAL for a usable suite): DO NOT call this tool with raw un-tested steps. EVERY step you send MUST have its "response" and "extract" fields populated from a live run. These are NOT optional. Without them: - The UI cannot render the step (shows an empty panel). - The rerecord runs blind and fails. - The step's {{variables}} won't resolve. Required per-step fields when calling this tool (in steps_json): • name, method, url, headers, assert — obviously • body — for POST/PUT/PATCH; MUST reference random inputs as {{varname}} placeholders, NOT inline timestamps. Inline timestamps get baked into the suite and collide on re-run. • extract — MUST contain a resolvable entry for every {{varname}} you reference in body/url/headers. JS-function entries are fine (they're the canonical "dynamic input" shape); JSONPath entries chain values from one step's response into later steps. Example: body has {"user_id":"alice_{{genUserId}}"} → step's extract must have {"genUserId":"function genUserId(){ ... }"}. • response — the raw captured response from your local curl. Shape: {"body":"<raw string>","status":201,"headers":{"Content-Type":"application/json",...}}. MANDATORY validate-locally flow (do this BEFORE calling create_test_suite): 1. Bring the dev's app up locally (Bash: docker compose up -d, or instruct the dev). Wait for /health readiness. 2. For EACH step in order (simulating what the runner will do): a. For dynamic inputs (user_id, timestamps, uuids): DON'T inline a value — write a JS function into the step's `extract` map, e.g. {"genUserId":"function genUserId(){return 'alice_'+Date.now()+'_'+Math.random().toString(36).slice(2,8);}"}, and reference it in body/url/headers/assertion-expected as {{genUserId}}. For the local curl, you still need a CONCRETE value for that run — so as you're building the step, JS-eval the function yourself (or just pick a value consistent with the function's output shape) to do ONE concrete local curl for capturing the response. That concrete value goes ONLY into the captured "response" body — NOT into `extract` (which keeps the JS function verbatim). b. Substitute {{name}} everywhere in the step's url/body/headers using accumulated variables (this step's extract + earlier steps' extract results). c. curl the SUBSTITUTED request against the live app. Capture the response. d. Check each "assert" against the captured response. If any fails → regenerate (different inputs / loosen assertion / change body shape) and retry this step. DO NOT move on with a failing step. e. Save the captured response into the step's "response" field as {"body":"<raw string>","status":<int>,"headers":{...}}. f. If the step has JSONPath entries in `extract`, evaluate each path against the response and note those values so later steps can use them in their {{var}} substitutions. 3. AFTER the first pass of all steps, run the WHOLE SEQUENCE a SECOND TIME against the same live app — no DB wipe in between. Because you're using JS-function generators, each run should pick fresh random inputs → no unique-constraint collision. If ANY step that passed the 1st run fails the 2nd run (common symptom: 500 "failed to save order" / "duplicate key" / "already exists"), the suite is NOT idempotent. Go back to step 2a and either (i) increase the entropy of the JS function, (ii) restructure the step to be READ-AFTER-WRITE instead of POST-then-POST, (iii) drop the step if it genuinely can't be made idempotent. 4. Only once every step passes BOTH validation runs → call create_test_suite. Pass each step's response + extract (with JS functions verbatim) through steps_json. If you call create_test_suite without response + extract on every step, you are creating a suite that is broken by construction. The UI + rerecord WILL fail. SELF-CONTAINED TESTS (required for repeat runs): * The suite will be re-run many times (local validation + record + sandbox replay + ad-hoc UI runs). It must not depend on prior state. * Put random inputs in `extract` JS functions with high entropy (timestamps, uuid). Plain "alice" will collide on re-run against producers with dedupe. * Prefer READ-AFTER-WRITE chaining: POST creates resource → extract id → GET uses id. Validates without depending on PRE-EXISTING ambient seed data (rows that "happen to exist" in the dev's DB). SEED → TESTED → CLEANUP roles within a suite: When the scenario is "user can read X" or "user can list X", you can't assert against ambient state — there's no guarantee the X exists when the suite runs. Pattern: step seed: POST /X (with dynamic {{var}} body) → extract id step tested: GET /X (or list) → assert against the seeded id step cleanup: DELETE /X/{{id}} → restore baseline Only the "tested" step is what the suite is FOR; the seed and cleanup steps are scaffolding so the test can run any number of times against any starting state. Without an explicit seed step, you're either testing nothing (empty list) or relying on pre-existing data the next replay won't have. DO NOT assert "the user has 3 orders" — that's ambient state. Seed N orders inside the suite first, then assert the count. Same applies to any "list / search / count" scenario: seed the data the test depends on, never assume it's there. ═══════════════════════════════════════════════════════════════════ SUBSTITUTION RULES — where {{var}} is and isn't allowed ═══════════════════════════════════════════════════════════════════ `extract` values come in two flavours and they substitute very differently: TYPE A — JS-function generator (`extract: { genUserId: "function genUserId(){return 'apple_'+Date.now()}" }`): The runtime STORES the source string and RE-RUNS the function on EVERY `{{genUserId}}` substitution site. Each call returns a fresh value. ONLY safe in POST / PUT / PATCH request BODIES — that's the one place you actually want a fresh value (uniqueness for inserts). TYPE B — JSONPath extract (`extract: { createdId: "$.order.user_id" }`): Evaluated ONCE against the step's recorded response, the resulting STRING is stored. Subsequent `{{createdId}}` substitutions resolve to that same fixed string. Safe everywhere — URLs, assertions, downstream bodies. ALLOWED placements for `{{generatorFn}}` (TYPE A): ✓ POST / PUT / PATCH request body — the canonical "give me a fresh value to insert" use case. FORBIDDEN placements for `{{generatorFn}}` (TYPE A) — the validator REJECTS these (generator-placement checks): ✗ `assert[*].expected` — the assertion's expected value will be a fresh function call, NOT the value the body sent. Static literals or `{{TYPE_B_extract}}` only. ✗ GET / DELETE / HEAD / PUT / PATCH URL (path or query) — those target an existing resource; the URL must encode the SAME id the creating POST used. Use a TYPE B extract from the creating step. ✗ Path/query of a downstream step's URL when the value should match what the upstream step inserted — same reason. CANONICAL PATTERN — read-after-write with a stable id: Step 0 (POST creates resource): body: {"user_id":"{{genUserId}}","name":"widget"} // TYPE A in body — fresh per run, OK extract: {"genUserId":"function genUserId(){...}", // TYPE A — body source "createdId":"$.order.user_id"} // TYPE B — capture server's stored id assert: [{type:"status_code", expected:"201"}, {type:"json_equal", key:"$.order.id", expected:"{{createdId}}"}] // TYPE B in assertion — stable Step 1 (GET reads it back): url: "/api/orders?user_id={{createdId}}" // TYPE B in GET URL — stable assert: [{type:"json_equal", key:"$.orders.0.user_id", expected:"{{createdId}}"}] // TYPE B — stable DO NOT do this (the validator will reject it): Step 0: body: {"user_id":"{{genUserId}}"} assert: [{type:"json_equal", key:"$.order.user_id", expected:"{{genUserId}}"}] // generator-placement check — TYPE A in assertion Step 1: url: "/api/orders?user_id={{genUserId}}" // generator-placement check — TYPE A in GET URL Name-collision check — do NOT pick an `extract` key that already exists on the app's appLevelCustomVariables. Use get_app_testing_context (or check the app payload) to enumerate them first; if a collision is unavoidable, scope-suffix your key (e.g. `genUserId_smokeTest`). Otherwise the runtime resolves the app-level variable first and silently shadows the suite's extract. You can also construct steps from data fetched via download_recording or get_app_testing_context, but the validate-locally-before-inserting rule still applies. CRITICAL — READING EXISTING SUITES: when the data you fetch via getTestSuite / get_app_testing_context / download_recording shows steps with `extract_variables` populated, that's the runtime's POST-EXECUTION SNAPSHOT (resolved values the runner wrote back for UI display). It is NOT what was authored. Treating that field as a copy-paste template makes the validator's extract_variables-input rejection reject every suite you produce. To replicate the authored behavior: copy every entry into `extract` instead, preserving keys and values verbatim (JS-function strings stay JS, JSONPath strings stay JSONPath). When in doubt: `extract_variables` is read-only output state; `extract` is input. ===== FROM-SCRATCH SCOPE RULE ===== When the dev asks to "generate / create / add / build keploy tests" without narrowing the scope, DEFAULT = ALL ENDPOINTS. Enumerate every non-trivial endpoint the app exposes (OpenAPI spec, router code, handler files) and author ONE suite per logical grouping — e.g. "user-crud", "auth-flow", "order-happy-path", "order-validation-errors". A single-endpoint app might produce one suite; a typical microservice produces 3-8. Groupings should be READ-AFTER-WRITE coherent (each suite's steps chain via extract variables rather than depending on outside state). TELL THE DEV up-front how many suites you're about to create and what each covers, then proceed — do NOT ask for confirmation mid-flow. If the dev explicitly narrows it ("just the happy path for orders", "only the auth flow"), honor that. ===== HARD RULE — NO DB-STATE-DEPENDENT STEPS ===== Do NOT include any step whose response body depends on total DB / queue / file-system state. Concretely: GET /items with no filter, GET /orders with no user_id filter, any "list-all" / "count" / "search" that returns more rows the longer the app has been running, any endpoint returning the CURRENT time / UUID / request-id. The auto-replay after record byte-compares the recorded response with what the live app returns under mocks, and non-deterministic bodies make gate 2 skip → the suite is never linked → sandbox replay fails with "no sandboxed tests". If you find yourself reasoning "this list might vary slightly but the mock should handle it" — STOP and drop the step. The suite should contain ONLY steps whose response body is fully determined by that step's own request: health checks, create-with-fresh-ids, read-back-by-id for the ids you just minted, validation-error 400s on bad payloads. Filtered reads using a freshly-extracted id are fine; unfiltered reads are not. ===== SERVER-SIDE IDEMPOTENCY ENFORCEMENT ===== This tool REJECTS (with a typed error, before creating anything) any suite whose mutating steps aren't idempotent on re-run. The rule: For each step with method ∈ {POST, PUT, PATCH} and a non-empty body, the body MUST contain at least one `{{name}}` placeholder that resolves to a per-run dynamic value. "Dynamic" means one of: (a) a JS-function entry in any step's `extract` map (e.g. {"genUserId": "function genUserId(){ return 'u_'+Date.now()+'_'+Math.random().toString(36).slice(2,8); }"}), OR (b) a JSONPath extract output from an EARLIER step (transitively dynamic if that step's own body was idempotent). If the endpoint is GENUINELY idempotent (e.g. POST /auth/refresh, PUT /tags/apply-same-input — repeat calls don't hit unique constraints) set `"idempotent": true` on the step to waive the check. Use this sparingly — the default is "assume it'll collide" because that's the common case. On rejection the error names the offending step and lists the dynamic variable names already in scope so you can see what's wireable. Fix the suite and retry — do NOT just flip `idempotent: true` to bypass. ===== MANDATORY OUTPUT — Phase 1 section ===== After all create_test_suite calls in a FROM-SCRATCH flow succeed, your final message to the dev MUST contain a section with this exact heading (do NOT collapse into prose; emit even for a single suite): ### Phase 1 — Inserted suites | Suite name | suite_id | Step count | | --- | --- | --- | | <name> | <suite_id> | <N> | One row per suite created in this flow. Next step after Phase 1 is record_sandbox_test (see its description for Phase 2). ===== HOW THIS TOOL ACTUALLY INSERTS THE SUITE ===== This tool DOES NOT POST the suite to api-server itself. It returns a "playbook" — a small array of shell steps for you (Claude) to walk via Bash. The playbook spawns the enterprise CLI `keploy create-test-suite` which: 1. Reads the suite JSON the playbook wrote to disk. 2. Runs every static structural check — exits 1 with violations on stdout if anything fails. 3. Fires the suite against the dev's local app TWICE (idempotency check) — exits 1 if the second run diverges from the first. 4. Runs dynamic checks (generator-dynamism + GET-coupling) — exits 1 with violation messages on failure. 5. POSTs the validated suite to api-server (HTTP 201 → success; HTTP 426 → CLI is older than api-server's rule set, dev needs to upgrade `keploy`). Walk the playbook in order. 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Intertext is left-aligned at the document margin while equations remain centered: ``` $$\aligned{ x &= a \\ \intertext{where} a &= b + c }$$ ``` `\tag` works on aligned blocks — the tag is right-justified and vertically centered: ``` $$\aligned{ f(x) &= x^2 + 2x + 1 \\ &= (x + 1)^2 } \tag{7}$$ ``` ### Boxed ``` $$ \boxed{E = mc^2} $$ ``` Draws a box-drawing frame around the content. ### Phantom ``` $$ a + \phantom{bbb} + c $$ ``` Invisible placeholder — renders as whitespace with the same dimensions as the content. ### Smash ``` $$ \sqrt{\smash{y^3}} $$ ``` `\smash{content}` renders content but collapses its height to a single line (the baseline row). Used to prevent tall content from affecting surrounding constructs like roots or delimiters. ### Substack ``` $$ \sum_{\substack{i=1 \\ j>0}} x_{ij} $$ ``` Stacks multiple lines vertically (for multi-line subscripts/superscripts). ### Tag ``` $$ E = mc^2 \tag{1} $$ ``` Equation tag rendered as `(text)`. ### Number Theory ``` $$ a \equiv b \pmod{n} $$ $$ a \bmod n \quad a \mid b $$ $$ \binom{n}{k} $$ ``` ### Style Commands (No-ops) `\displaystyle`, `\textstyle`, `\scriptstyle`, `\scriptscriptstyle` are accepted but transparent (Hyades has no math size concept). `\notag` and `\nonumber` are also silently ignored. This allows pasting LaTeX source that uses these commands without errors. ### Math Spacing `\!` (negative thin), `\,` (thin), `\:` (medium), `\;` (thick), `\quad` (1em), `\qquad` (2em) ### Atom-Type Overrides (\mathord, \mathbin, \mathrel) Override the default spacing category of a symbol. Analogous to TeX's `{=}` idiom for suppressing operator spacing, but explicit and readable: ``` $a \mathord{=} b$ %% "a=b" — = treated as ordinary symbol (no spacing) $a = b$ %% "a = b" — default relation spacing $f \mathrel{:} A \to B$ %% "f : A → B" — : treated as relation (symmetric spacing) $a : b$ %% "a: b" — default punctuation spacing $a \mathbin{\triangle} b$ %% "a △ b" — triangle with binary operator spacing ``` - `\mathord{X}`: Suppress spacing — X renders as an ordinary symbol with no surrounding gaps. Use this instead of TeX's `{=}` or `{}=` idiom which does not work in Hyades. - `\mathbin{X}`: Force binary operator spacing (gap on both sides). - `\mathrel{X}`: Force relation spacing (gap on both sides). ### Binary Operators `\oplus`, `\otimes`, `\odot`, `\circ`, `\bullet`, `\star`, `\dagger`, `\ddagger` ### Geometry `\angle`, `\triangle`, `\perp`, `\parallel` ### Famous Equations (all valid input) ``` $$ x = \frac{-b \pm \sqrt{b^2 - 4ac}}{2a} $$ %% Quadratic formula $$ e^{i\pi} + 1 = 0 $$ %% Euler's identity $$ f(x) = \frac{1}{\sigma\sqrt{2\pi}} e^{-\frac{(x-\mu)^2}{2\sigma^2}} $$ %% Normal distribution $$ \fn{Attention}(Q, K, V) = \fn{softmax}\left(\frac{QK^\top}{\sqrt{d_k}}\right) V $$ %% Attention mechanism $$ e^x = \sum_{n=0}^{\infty} \frac{x^n}{n!} $$ %% Taylor series $$ \int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi} $$ %% Gaussian integral $$ P(A|B) = \frac{P(B|A) P(A)}{P(B)} $$ %% Bayes' theorem $$ \nabla \times \mathbf{E} = -\frac{\partial \mathbf{B}}{\partial t} $$ %% Maxwell's equation $$ i\hbar \frac{\partial}{\partial t} \Psi = \hat{H} \Psi $$ %% Schrodinger equation $$ \fn{softmax}(x_i) = \frac{e^{x_i}}{\sum_j e^{x_j}} $$ %% Softmax ``` --- ## Text Formatting ``` \textbf{bold text} \textit{italic text} \texttt{monospace text} \textbf{\textit{bold italic}} ``` Nesting `\textbf` and `\textit` produces bold-italic text. Inline math `$...$` inside `\textit` or `\textbf` is rendered as math (not styled as text): ``` \textit{Let $f(x) = x^2$ be a function} ``` ### Verbatim (No Processing) ``` \verb|raw \commands { } are preserved| ``` ### Special Characters `\textbackslash` → \, `\textdollar` → $, `\textpercent` → %, `\textampersand` → &, `\texthash` → # ### Text Spacing Commands `\ ` (backslash-space) — explicit inter-word space. Useful after abbreviations: `i.e.\ $f$` renders without extra sentence spacing. `\@` — marks the next period as sentence-ending (silently consumed). `\,` — thin space (works in both text and math mode). --- ## Paragraphs and Line Breaking Text flows into paragraphs automatically. A single newline is a space; a blank line starts a new paragraph. ### Line-Breaking Modes ``` \linebreaker{greedy} % Default. Fast, good results. \linebreaker{knuth} % TeX-style optimal. Minimizes ugliness. \linebreaker{raggedright} % Left-aligned, no justification. ``` ### Hyphenation `\sethyphenate{true}` / `\sethyphenate{false}` --- ## Tables Tables use `\table` with nested `\row` and `\col`: ``` \table[width:40, frame:single, pad:{l:1,r:1}]{ \row[frame:{b:double}]{ \col{Name} \col{Value} } \row{ \col{Alpha} \col{0.05} } \row{ \col{Beta} \col{0.95} } } ``` ### Table Properties | Property | Values | Default | |----------|--------|---------| | `width` / `w` | number, `auto` | parent width | | `frame` / `f` | `none`, `dotted`, `single`, `rounded`, `double`, `bold` | `single` | | `border` | same as frame (outer edges only) | unset | | `pad` / `p` | number or `{t:N, b:N, l:N, r:N}` | 0 | | `align` / `a` | `l`/`left`, `c`/`center`, `r`/`right` | `l` | | `valign` / `va` | `t`/`top`, `m`/`middle`, `b`/`bottom` | `t` | Row properties: `frame`, `pad`, `align`, `valign`, `height`. Column properties: `width`, `align`, `valign`, `frame`, `pad`, `span`, `reset`. Frame styles: `none` (space), `dotted` (┄┆), `single` (─│), `rounded` (╭╮╰╯ corners), `double` (═║), `bold` (━┃) Compound edges: `frame:{t:double, b:single, l:none, r:none}`, `pad:{l:1, r:1}` Properties cascade: table → column (down rows) → row → cell. IMPORTANT: When a row overrides a property (e.g. `frame:{b:double}`), that override is inherited by ALL subsequent rows. To stop it, the next row must explicitly reset it (e.g. `frame:{b:single}`). The `border` property on the table level controls the outer edges and cannot be overridden by row or column `frame`. --- ## Lists ``` \fancylist{ - First item - Second item with longer text that wraps to the next line - Third item - Nested child - Grandchild } ``` Three nesting levels supported. Uses ●/○ bullets in Unicode, - in ASCII. --- ## Layout Primitives Flex-like box model for spatial control. ### Box Types ``` \begin[width]{hbox} % horizontal (side by side) \child[width][align]{content} \end{hbox} \begin[top|middle|bottom]{hbox} % hbox with vertical alignment \child[width][align]{content} \end{hbox} \begin[width]{vbox} % vertical (stacked) \child[width][align]{content} \end{vbox} ``` Child width: fixed number, `auto` (fill remaining), `intrinsic` (natural width), or omitted (equal share). When multiple children omit width, they split the remaining space equally (after fixed-width children). Horizontal alignment: `left`, `center`, `right`. Vertical alignment for hbox: set on `\begin` bracket — `top` (default), `middle`, `bottom`. Width inheritance: boxes without an explicit width inherit their parent's width. `\setwidth{N}` sets the document-level width. ### Rules ``` \hrule[width]{left_cap}{fill_char}{right_cap} \vrule[height]{top}{fill}{bottom} \intersect_rules{...} % fix junction characters at rule crossings ``` Width/height can be a number or `auto`. An `auto`-width `\hrule` in a vbox stretches to the box width. An `auto`-height `\vrule` in an hbox stretches to match the tallest sibling. `\intersect_rules` scans all cells, checks neighboring line arms, and replaces with correct junction glyphs (┌ ┬ ┐ ├ ┼ ┤ └ ┴ ┘). Handles single, double, bold, and mixed styles. ### Measuring Content ``` \measure<content_name,width_var,height_var>{content to measure} ``` Renders content invisibly, stores it under `content_name` (retrieve with `\recall<content_name>`), and stores the measured width and height into integer variables. ### Spacing `\vskip{N}` (N blank lines), `\hskip{N}` (N spaces) ### Common Layout Patterns Two-column with gutter: ``` \begin{hbox} \child{Left column} \child[2]{} \child{Right column} \end{hbox} ``` Centering via auto spacers: ``` \begin{hbox} \child[auto]{} \child[intrinsic]{Centered content} \child[auto]{} \end{hbox} ``` Indentation: ``` \begin{hbox} \child[4]{} \child[auto]{Indented content} \end{hbox} ``` --- ## User-Defined Macros ``` \macro<\greet{name}>{Hello, ${name}!} \greet{World} % → Hello, World! \macro<\fullname{first}{last}>{${first} ${last}} \fullname{John}{Doe} % → John Doe % Optional parameters with defaults \macro<\heading[char=-]{title}>{ ${title} \hrule[20]{}{${char}}{} } \heading{Default} % uses - \heading[char:=]{Custom} % uses = ``` --- ## Document Settings ``` \setwidth{80} % Output width in columns (default: 80) \setunicode{true} % Use Unicode symbols (default: true) \setmathitalic{true} % Italicize math variables (default: true) \linebreaker{greedy} % Line-breaking algorithm \sethyphenate{true} % Enable hyphenation \setparskip{1} % Blank lines between paragraphs \setmathabove{1} % Blank lines above display math (default: 0) \setmathbelow{1} % Blank lines below display math (default: 0) ``` --- ## Computation Variables, loops, and conditionals are available. ### Variables and Arithmetic ``` \let<x>{10} \let<y>{20} \let<sum>{\add{\valueof<x>,\valueof<y>}} Result: \valueof<sum> % → Result: 30 ``` ### Conditionals ``` \let<n>{42} \if{\gt{\valueof<n>,0}}{positive}\else{non-positive} ``` ### Loops ``` \let<i>{1} \begin{loop} \exit_when{\gt{\valueof<i>,5}} \valueof<i>\hskip{1} \inc<i> \end{loop} % Output: 1 2 3 4 5 ``` ### Content Storage `\assign<name>{content}` stores text, `\recall<name>` retrieves it. `\let`/`\valueof` is for integers; `\assign`/`\recall` is for text. ### Lambdas ``` \lambda<double>[x]{\mul{\recall<x>,2}} \recall<double>[5] % → 10 ``` ### Arrays ``` \let<nums[]>{[10, 20, 30]} \valueof<nums>[0] % → 10 \len<nums> % → 3 \push<nums>{40} % append ``` --- ## Quick Reference ### Math Mode | Input | Output | |-------|--------| | `$x^2$` | x² | | `$x_i$` | xᵢ | | `$\frac{a}{b}$` | a/b (stacked) | | `$\sqrt{x}$` | √x | | `$\sum_{i=1}^n$` | Σ with limits | | `$\int_a^b$` | ∫ with limits | | `$\prod_{i=1}^n$` | ∏ with limits | | `$\lim_{x \to 0}$` | lim with subscript below | | `$\limsup_{n}$` | lim sup with subscript below | | `$\liminf_{n}$` | lim inf with subscript below | | `$\alpha, \beta, \gamma$` | α, β, γ | | `$\mathbb{R}$` | ℝ | | `$\mathbf{v}$` | 𝐯 | | `$\leq, \geq, \neq$` | ≤, ≥, ≠ | | `$\in, \forall, \exists$` | ∈, ∀, ∃ | | `$\rightarrow, \Rightarrow$` | →, ⇒ | | `$\infty, \partial, \nabla$` | ∞, ∂, ∇ | | `$f'(x)$` | 𝑓′(𝑥) | | `$\binom{n}{k}$` | binomial coefficient | | `$\lfloor x \rfloor$` | ⌊x⌋ | | `$\fn{name}$` | custom function name | | `$\operatorname{name}$` | same as \fn | | `$\text{words}$` | upright text in math | | `$\ll, \gg$` | ≪, ≫ | | `$\mathord{=}$` | suppress operator spacing | | `$\mathbin{:}$` | force binary operator spacing | | `$\mathrel{:}$` | force relation spacing | | `$\prec, \succ$` | ≺, ≻ | | `$\neg, \land, \lor$` | ¬, ∧, ∨ | | `$\subseteq, \setminus$` | ⊆, ∖ | | `$\mid$` | ∣ (divides) | | `$\therefore, \because$` | ∴, ∵ | | `$\wp, \imath, \jmath$` | ℘, ı, ȷ | | `$\Box$` | □ | | `$\not=$` | ≠ (\not prefix negates relations) | | `$\left.\right\|$` | invisible delimiter (evaluation bar) | | `$\overset{n}{=}$` | annotation above base | | `$\underset{x}{y}$` | annotation below base | | `$\boxed{x}$` | framed box around content | | `$\phantom{x}$` | invisible spacer | | `$\smash{x}$` | collapse height to baseline | | `$\xrightarrow{f}$` | extensible arrow with label | | `$\substack{a \\ b}$` | stacked lines | | `$\mathfrak{R}$` | Fraktur (𝔄𝔅ℭ) | | `$\mathsf{A}$` | sans-serif (𝖠𝖡𝖢) | | `$\boldsymbol{\alpha}$` | bold Greek (𝛂𝛃) | | `$\coloneqq$` | ≔ (definition) | | `$\eqqcolon$` | ≕ (reverse definition) | | `$a := b$` | ≔ (combined relation) | ### Text Commands | Command | Effect | |---------|--------| | `\textbf{x}` | **bold** | | `\textit{x}` | *italic* | | `\texttt{x}` | monospace | | `\verb\|x\|` | verbatim | | `\hrule` | horizontal line | | `\vskip{N}` | N blank lines | | `\hskip{N}` | N spaces | ### Table Syntax ``` \table[width:W, frame:STYLE, pad:{l:L,r:R}, border:STYLE, align:A]{ \row[frame:{b:STYLE}]{ \col[width:N, align:A]{content} } } ``` ### Layout Syntax ``` \begin[width]{vbox} \child[width][h_align]{content} \end{vbox} \begin[top|middle|bottom]{hbox} \child[width][h_align]{content} \end{hbox} ``` ### Settings ``` \setwidth{N} \setunicode{true|false} \setmathitalic{true} \linebreaker{greedy|knuth|raggedright} \sethyphenate{true} \setparskip{N} \setmathabove{N} \setmathbelow{N} ```
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  • Submit a URL for NHS to crawl and score. Use when you discover an agent-first tool, API, or service that isn't in the index yet. NHS will fetch the site, check its 7 agentic signals (llms.txt, ai-plugin.json, OpenAPI, structured API, MCP server, robots.txt AI rules, Schema.org), compute a score, and add it to the index. The site becomes searchable within a few seconds if the crawl succeeds.
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  • Get a comprehensive energy profile for a US state from the EIA. Returns an overview of energy production, consumption, prices, and expenditures across all fuel types for the specified state. Useful for understanding a state's full energy landscape. Args: state: Two-letter US state abbreviation (e.g. 'CA', 'TX', 'NY').
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  • Get petroleum and oil price or production data from the EIA. Returns time series data for petroleum products including crude oil prices, production volumes, imports, exports, and refinery operations. Args: series: EIA series ID for the petroleum data. Common series: 'PET.RWTC.D' (WTI crude oil daily price), 'PET.RBRTE.D' (Brent crude oil daily price), 'PET.EMM_EPMR_PTE_NUS_DPG.W' (US regular gasoline weekly price), 'PET.MCRFPUS2.M' (US crude oil production monthly). Default is 'PET.RWTC.D'. limit: Maximum number of records to return (default 100, max 5000).
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  • Get electricity generation, consumption, or price data from the EIA. Returns data on electricity production, retail sales, prices, and fuel consumption for power generation across US states and sectors. Args: state: Two-letter US state abbreviation (e.g. 'CA', 'TX'). Omit for national data. sector: Sector filter. Common values: 'RES' (residential), 'COM' (commercial), 'IND' (industrial), 'TRA' (transportation), 'ALL' (all sectors). frequency: Data frequency: 'monthly', 'quarterly', or 'annual'. Default is 'monthly'. limit: Maximum number of records to return (default 100, max 5000).
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  • Surgically update ANY field in a skill or solution definition, redeploy, and optionally re-test — all in one step. SUPPORTED OPERATIONS: 1. Scalar (dot notation): { "problem.statement": "new value", "role.persona": "You are..." } 2. Deep nested: { "intents.thresholds.accept": 0.9, "policy.escalation.enabled": true } 3. Array push: { "tools_push": [{ name: "new_tool", description: "..." }] } 4. Array delete: { "tools_delete": ["tool_name"] } 5. Array update: { "tools_update": [{ name: "existing_tool", description: "updated" }] } 6. Replace whole section: { "role": { persona: "...", goals: [...] } } EXAMPLES: - Change persona (full replace): updates: { "role.persona": "You are a friendly assistant" } - Append to persona (don't replace): updates: { "persona_append": "\n\nALWAYS respond in 2 sentences." } - Add a guardrail: updates: { "policy.guardrails.never_push": ["Never share passwords"] } - Update problem: updates: { "problem.statement": "...", "problem.goals": ["goal1"] } - Add a tool: updates: { "tools_push": [{ name: "conn.tool", description: "...", inputs: [...], output: {...} }] } - Change intent: updates: { "intents.supported_update": [{ id: "i1", description: "new desc" }] } - Force redeploy: updates: { "_force_redeploy": true } - CREATE a new skill: target='skill', skill_id='my-new-skill', updates: { "problem.statement": "...", "role.persona": "..." } If the skill doesn't exist yet, a default scaffold is created and the updates are applied on top. The skill is automatically added to the solution topology. Use target='skill' + skill_id for skill fields. Use target='solution' for solution-level fields (linked_skills, platform_connectors, ui_plugins).
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