fix(knowledge_sql): match write keywords on word boundaries (allow valid SELECTs) (#640)

* fix(knowledge_sql): match write keywords on word boundaries

The read-only guard rejected a query if any of DROP/DELETE/INSERT/UPDATE/
ALTER/CREATE/ATTACH appeared as a bare substring of the uppercased text. That
wrongly blocks valid SELECTs whose column/alias/literal merely contains one --
e.g. "deleted_at" (DELETE), "created_at" (CREATE), "updated_content" (UPDATE).
The knowledge_chunks table actually has deleted_at/created_at columns and the
store's own retrieval filters on "WHERE deleted_at IS NULL", so realistic
read queries were refused. Match on word boundaries with a compiled regex,
mirroring the sibling tool db_query.py. Add a regression test.

* fix(knowledge_sql): ignore string literals in keyword scan, broaden error handling

- Strip single-quoted literals before the forbidden-keyword scan so
  SELECTs whose data merely mentions a write keyword (e.g. LIKE
  '%delete%') are not rejected.
- Catch sqlite3.Error instead of only OperationalError so multi-
  statement strings return a failed ToolResult instead of raising.
- Document created_at/deleted_at in the tool's schema description.

---------

Co-authored-by: Elliot Slusky <elliot@slusky.com>

.github/clone-stats/badge.json

@@ -1,7 +1,7 @@
 {
   "schemaVersion": 1,
   "label": "Git Clones",
-  "message": "142,750",
+  "message": "159,322",
   "color": "green",
   "namedLogo": "git"
 }

.github/clone-stats/clone-data.json

@@ -1,6 +1,6 @@
 {
-  "total_clones": 142750,
-  "last_updated": "2026-07-06T10:14:21Z",
+  "total_clones": 159322,
+  "last_updated": "2026-07-16T08:08:14Z",
   "daily": {
     "2026-03-27": 2189,
     "2026-03-28": 1874,
@@ -102,6 +102,16 @@
     "2026-07-02": 593,
     "2026-07-03": 537,
     "2026-07-04": 411,
-    "2026-07-05": 485
+    "2026-07-05": 485,
+    "2026-07-06": 555,
+    "2026-07-07": 905,
+    "2026-07-08": 1171,
+    "2026-07-09": 1857,
+    "2026-07-10": 1181,
+    "2026-07-11": 2185,
+    "2026-07-12": 1917,
+    "2026-07-13": 2102,
+    "2026-07-14": 2337,
+    "2026-07-15": 2362
   }
 }

README.md

@@ -4,7 +4,7 @@
   <p><i>Personal AI, On Personal Devices.</i></p>
 
   <p>
-    <a href="https://scalingintelligence.stanford.edu/blogs/openjarvis/"><img src="https://img.shields.io/badge/project-OpenJarvis-blue" alt="Project"></a>
+    <a href="https://openjarvis.stanford.edu/"><img src="https://img.shields.io/badge/project-OpenJarvis-blue" alt="Project"></a>
     <a href="https://open-jarvis.github.io/OpenJarvis/"><img src="https://img.shields.io/badge/docs-mkdocs-blue" alt="Docs"></a>
     <img src="https://img.shields.io/badge/python-%3E%3D3.10-blue" alt="Python">
     <img src="https://img.shields.io/badge/license-Apache%202.0-green" alt="License">
@@ -23,7 +23,7 @@
 
 > **[Documentation](https://open-jarvis.github.io/OpenJarvis/)**
 >
-> **[Project Site](https://scalingintelligence.stanford.edu/blogs/openjarvis/)**
+> **[Project Site](https://openjarvis.stanford.edu/)**
 >
 > **[Paper](https://arxiv.org/abs/2605.17172)**
 >

docs/index.md

@@ -215,7 +215,7 @@ OpenJarvis is built around five composable layers. Each has a clean interface an
 
 OpenJarvis is part of [Intelligence Per Watt](https://www.intelligence-per-watt.ai/), a research initiative studying the efficiency of on-device AI systems. Developed at [Hazy Research](https://hazyresearch.stanford.edu/) and the [Scaling Intelligence Lab](https://scalingintelligence.stanford.edu/) at [Stanford SAIL](https://ai.stanford.edu/).
 
-Read the [blog post](https://scalingintelligence.stanford.edu/blogs/openjarvis/) for the full research motivation, architecture details, and experimental results.
+Read the [blog post](https://openjarvis.stanford.edu/) for the full research motivation, architecture details, and experimental results.
 
 ## Citation
 

docs/leaderboard.md

@@ -55,5 +55,5 @@ See how the OpenJarvis community saves money, energy, and compute by running AI
 <div id="leaderboard-pagination" class="lb-pagination"></div>
 
 <p style="font-size:12px;opacity:0.6;margin-top:12px">
-*Dollar savings estimated vs. Claude Opus 4.6 API pricing ($5/1M input, $25/1M output tokens). Assumes local open-source models produce roughly the same number of tokens per request as cloud models.
+*Dollar savings estimated vs. Claude Fable 5 API pricing ($10/1M input, $50/1M output tokens). Assumes local open-source models produce roughly the same number of tokens per request as cloud models.
 </p>

frontend/src/components/Chat/SystemPanel.tsx

@@ -29,8 +29,8 @@ interface TelemetryStats {
 }
 
 const CLOUD_PRICING = [
-  { name: 'GPT-5.3', input: 2.00, output: 10.00, primary: true },
-  { name: 'Claude Opus 4.6', input: 5.00, output: 25.00, primary: false },
+  { name: 'GPT-5.6 Sol', input: 5.00, output: 30.00, primary: true },
+  { name: 'Claude Fable 5', input: 10.00, output: 50.00, primary: false },
   { name: 'Gemini 3.1 Pro', input: 2.00, output: 12.00, primary: false },
 ];
 

frontend/src/components/Dashboard/CostComparison.tsx

@@ -2,8 +2,8 @@ import { DollarSign, TrendingDown, Cloud, HardDrive } from 'lucide-react';
 import { useAppStore } from '../../lib/store';
 
 const CLOUD_PRICING = [
-  { name: 'GPT-5.3', input: 2.00, output: 10.00 },
-  { name: 'Claude Opus 4.6', input: 5.00, output: 25.00 },
+  { name: 'GPT-5.6 Sol', input: 5.00, output: 30.00 },
+  { name: 'Claude Fable 5', input: 10.00, output: 50.00 },
   { name: 'Gemini 3.1 Pro', input: 2.00, output: 12.00 },
 ];
 

frontend/src/components/Desktop/SavingsDashboard.tsx

@@ -222,8 +222,8 @@ const styles: Record<string, React.CSSProperties> = {
 };
 
 const PROVIDER_COLORS: Record<string, string> = {
-  'gpt-5.3': colors.green,
-  'claude-opus-4.6': colors.yellow,
+  'gpt-5.6-sol': colors.green,
+  'claude-fable-5': colors.yellow,
   'gemini-3.1-pro': colors.accent,
 };
 

frontend/src/pages/AgentsPage.tsx

@@ -3740,8 +3740,8 @@ export function AgentsPage() {
               const paramsB = paramMatch ? parseFloat(paramMatch[1]) : 9;
               const flops = 2 * paramsB * 1e9 * (inTok + outTok);
               const providers = [
-                { label: 'GPT-5.3', inPer1M: 2.0, outPer1M: 10.0 },
-                { label: 'Claude Opus 4.6', inPer1M: 5.0, outPer1M: 25.0 },
+                { label: 'GPT-5.6 Sol', inPer1M: 5.0, outPer1M: 30.0 },
+                { label: 'Claude Fable 5', inPer1M: 10.0, outPer1M: 50.0 },
                 { label: 'Gemini 3.1 Pro', inPer1M: 2.0, outPer1M: 12.0 },
               ];
               const energyWh = (inTok + outTok) / 1000 * 0.4;

frontend/src/pages/SettingsPage.tsx

@@ -805,7 +805,7 @@ export function SettingsPage() {
               </p>
               <div className="flex gap-3 mt-3 text-xs">
                 <a
-                  href="https://scalingintelligence.stanford.edu/blogs/openjarvis/"
+                  href="https://openjarvis.stanford.edu/"
                   target="_blank"
                   rel="noopener noreferrer"
                   style={{ color: 'var(--color-accent)' }}

src/openjarvis/recipes/data/operators/openjarvis_twitter_bot_prompt.md

@@ -15,7 +15,7 @@ HARD RULE: Every reply MUST be ≤280 characters. Count before sending.
 - GitHub: https://github.com/open-jarvis/OpenJarvis
 - Docs: https://open-jarvis.github.io/OpenJarvis/
 - Discord: https://discord.gg/wfXEkpPX
-- Blog: https://scalingintelligence.stanford.edu/blogs/openjarvis/
+- Blog: https://openjarvis.stanford.edu/
 - Install: `git clone https://github.com/open-jarvis/OpenJarvis.git && cd OpenJarvis && uv sync`
 - CLI commands (ONLY these exist):
   - `jarvis init` — auto-detects hardware, configures engine

src/openjarvis/server/comparison.py

@@ -215,8 +215,8 @@ COMPARISON_HTML = """\
         <tr>
           <th></th>
           <th>OpenJarvis (Local)</th>
-          <th>GPT-5.3</th>
-          <th>Claude Opus 4.6</th>
+          <th>GPT-5.6 Sol</th>
+          <th>Claude Fable 5</th>
           <th>Gemini 3.1 Pro</th>
         </tr>
       </thead>
@@ -261,11 +261,11 @@ COMPARISON_HTML = """\
         <div class="cc-value">$0.00/mo</div>
       </div>
       <div class="calc-card cloud">
-        <div class="cc-label">GPT-5.3</div>
+        <div class="cc-label">GPT-5.6 Sol</div>
         <div class="cc-value" id="calc-gpt">--</div>
       </div>
       <div class="calc-card cloud">
-        <div class="cc-label">Claude Opus 4.6</div>
+        <div class="cc-label">Claude Fable 5</div>
         <div class="cc-value" id="calc-claude">--</div>
       </div>
       <div class="calc-card cloud">
@@ -292,13 +292,13 @@ COMPARISON_HTML = """\
 <script>
 // Embedded data -- avoids API calls, keeps the page static and fast.
 const CLOUD_PRICING = {
-  "gpt-5.3": {
-    input_per_1m: 2.00, output_per_1m: 10.00,
-    label: "GPT-5.3"
+  "gpt-5.6-sol": {
+    input_per_1m: 5.00, output_per_1m: 30.00,
+    label: "GPT-5.6 Sol"
   },
-  "claude-opus-4.6": {
-    input_per_1m: 5.00, output_per_1m: 25.00,
-    label: "Claude Opus 4.6"
+  "claude-fable-5": {
+    input_per_1m: 10.00, output_per_1m: 50.00,
+    label: "Claude Fable 5"
   },
   "gemini-3.1-pro": {
     input_per_1m: 2.00, output_per_1m: 12.00,
@@ -376,8 +376,8 @@ function updateTable() {
   const sc = SCENARIOS[activeScenario];
   const i = sc.avg_input_tokens, o = sc.avg_output_tokens;
   const c = sc.calls_per_month;
-  const gpt = calcMonthlyCost(c, i, o, 'gpt-5.3');
-  const claude = calcMonthlyCost(c, i, o, 'claude-opus-4.6');
+  const gpt = calcMonthlyCost(c, i, o, 'gpt-5.6-sol');
+  const claude = calcMonthlyCost(c, i, o, 'claude-fable-5');
   const gemini = calcMonthlyCost(c, i, o, 'gemini-3.1-pro');
 
   document.getElementById('t-gpt-m').textContent = fmtDollar(gpt);
@@ -410,8 +410,8 @@ function updateCalc() {
   const avgOut = tpc - avgIn;
   const callsPerMonth = cpd * 30;
 
-  const gpt = calcMonthlyCost(callsPerMonth, avgIn, avgOut, 'gpt-5.3');
-  const claude = calcMonthlyCost(callsPerMonth, avgIn, avgOut, 'claude-opus-4.6');
+  const gpt = calcMonthlyCost(callsPerMonth, avgIn, avgOut, 'gpt-5.6-sol');
+  const claude = calcMonthlyCost(callsPerMonth, avgIn, avgOut, 'claude-fable-5');
   const gemini = calcMonthlyCost(callsPerMonth, avgIn, avgOut, 'gemini-3.1-pro');
 
   document.getElementById('calc-gpt').textContent = fmtDollar(gpt) + '/mo';

src/openjarvis/server/dashboard.py

@@ -184,7 +184,7 @@ DASHBOARD_HTML = """\
   <div class="providers">
     <div class="provider-card openai">
       <div class="pname">OpenAI</div>
-      <div class="pmodel">GPT-5.3 &mdash; $2.00 / $10.00 per 1M tokens</div>
+      <div class="pmodel">GPT-5.6 Sol &mdash; $5.00 / $30.00 per 1M tokens</div>
       <div class="savings-amount" id="save-openai">$0.00</div>
       <div class="breakdown">
         <div class="item">
@@ -199,7 +199,7 @@ DASHBOARD_HTML = """\
     </div>
     <div class="provider-card anthropic">
       <div class="pname">Anthropic</div>
-      <div class="pmodel">Claude Opus 4.6 &mdash; $5.00 / $25.00 per 1M tokens</div>
+      <div class="pmodel">Claude Fable 5 &mdash; $10.00 / $50.00 per 1M tokens</div>
       <div class="savings-amount" id="save-anthropic">$0.00</div>
       <div class="breakdown">
         <div class="item">
@@ -281,12 +281,12 @@ DASHBOARD_HTML = """\
   <div class="providers-heading">Energy &amp; Compute Avoided</div>
   <div class="metrics-row">
     <div class="metric-card">
-      <div class="mheading">Energy Saved (vs GPT-5.3)</div>
+      <div class="mheading">Energy Saved (vs GPT-5.6 Sol)</div>
       <div class="mvalue green" id="energy-joules">0 <span class="munit">J</span></div>
       <div class="msub" id="energy-kwh">0 kWh of cloud datacenter energy avoided</div>
     </div>
     <div class="metric-card">
-      <div class="mheading">FLOPs Avoided (vs GPT-5.3)</div>
+      <div class="mheading">FLOPs Avoided (vs GPT-5.6 Sol)</div>
       <div class="mvalue purple" id="flops-val">0 <span class="munit">FLOP</span></div>
       <div class="msub" id="flops-sub">cloud compute operations not needed</div>
     </div>
@@ -354,8 +354,8 @@ async function refresh() {
       providerMap[p.provider] = p;
     });
 
-    // OpenAI / GPT-5.3
-    const oa = providerMap['gpt-5.3'] || {};
+    // OpenAI / GPT-5.6 Sol
+    const oa = providerMap['gpt-5.6-sol'] || {};
     document.getElementById('save-openai')
       .textContent = fmtDollar(oa.total_cost || 0);
     document.getElementById('save-openai-in')
@@ -363,8 +363,8 @@ async function refresh() {
     document.getElementById('save-openai-out')
       .textContent = fmtDollar(oa.output_cost || 0);
 
-    // Anthropic / Claude Opus 4.6
-    const an = providerMap['claude-opus-4.6'] || {};
+    // Anthropic / Claude Fable 5
+    const an = providerMap['claude-fable-5'] || {};
     document.getElementById('save-anthropic')
       .textContent = fmtDollar(an.total_cost || 0);
     document.getElementById('save-anthropic-in')
@@ -384,13 +384,13 @@ async function refresh() {
     // Monthly projections
     const proj = d.monthly_projection || {};
     document.getElementById('proj-openai')
-      .textContent = fmtDollar(proj['gpt-5.3'] || 0);
+      .textContent = fmtDollar(proj['gpt-5.6-sol'] || 0);
     document.getElementById('proj-anthropic')
-      .textContent = fmtDollar(proj['claude-opus-4.6'] || 0);
+      .textContent = fmtDollar(proj['claude-fable-5'] || 0);
     document.getElementById('proj-google')
       .textContent = fmtDollar(proj['gemini-3.1-pro'] || 0);
 
-    // Energy / FLOPs (use GPT-5.3 as reference)
+    // Energy / FLOPs (use GPT-5.6 Sol as reference)
     const ej = oa.energy_joules || 0;
     const eWh = oa.energy_wh || 0;
     const fl = oa.flops || 0;

src/openjarvis/server/savings.py

@@ -23,19 +23,19 @@ from openjarvis.core.types import TOKEN_COUNTING_VERSION  # noqa: E402,F401
 # ---------------------------------------------------------------------------
 
 CLOUD_PRICING: Dict[str, Dict[str, float]] = {
-    "gpt-5.3": {
-        "input_per_1m": 2.00,
-        "output_per_1m": 10.00,
-        "label": "GPT-5.3",
+    "gpt-5.6-sol": {
+        "input_per_1m": 5.00,
+        "output_per_1m": 30.00,
+        "label": "GPT-5.6 Sol",
         "provider": "OpenAI",
         "params_b": 200.0,
         "energy_wh_per_1k_tokens": 0.4,
         "flops_per_token": 3.0e12,
     },
-    "claude-opus-4.6": {
-        "input_per_1m": 5.00,
-        "output_per_1m": 25.00,
-        "label": "Claude Opus 4.6",
+    "claude-fable-5": {
+        "input_per_1m": 10.00,
+        "output_per_1m": 50.00,
+        "label": "Claude Fable 5",
         "provider": "Anthropic",
         "params_b": 137.0,
         "energy_wh_per_1k_tokens": 0.5,

src/openjarvis/tools/knowledge_sql.py

@@ -6,6 +6,7 @@ and filtering operations that BM25 search cannot handle.
 
 from __future__ import annotations
 
+import re
 import sqlite3
 from typing import Any, Optional
 
@@ -16,10 +17,25 @@ from openjarvis.tools._stubs import BaseTool, ToolSpec
 
 _MAX_ROWS = 50
 
+# Write keywords are matched on word boundaries (mirroring db_query.py) so that
+# a read-only SELECT is not rejected just because a column/alias/literal happens
+# to contain one as a substring (e.g. "deleted_at", "created_at").
+_FORBIDDEN_RE = re.compile(
+    r"\b(DROP|DELETE|INSERT|UPDATE|ALTER|CREATE|TRUNCATE|ATTACH)\b",
+    re.IGNORECASE,
+)
+
+# String literals are stripped before the keyword scan so that data mentioning
+# a write keyword (e.g. WHERE content LIKE '%delete%') is not rejected. A write
+# "hidden" in a literal still cannot execute: the query must start with SELECT
+# and sqlite3 refuses multi-statement strings.
+_STRING_LITERAL_RE = re.compile(r"'[^']*'")
+
 _SCHEMA_DESCRIPTION = (
     "Table: knowledge_chunks\n"
     "Columns: id, content, source, doc_type, doc_id, title, author, "
-    "participants, timestamp, thread_id, url, metadata, chunk_index"
+    "participants, timestamp, thread_id, url, metadata, chunk_index, "
+    "created_at, deleted_at (NULL for active rows)"
 )
 
 
@@ -84,21 +100,20 @@ class KnowledgeSQLTool(BaseTool):
                 success=False,
             )
 
-        _FORBIDDEN = ("DROP", "DELETE", "INSERT", "UPDATE", "ALTER", "CREATE", "ATTACH")
-        for forbidden in _FORBIDDEN:
-            if forbidden in normalized:
-                return ToolResult(
-                    tool_name="knowledge_sql",
-                    content=(
-                        f"Query contains forbidden keyword: {forbidden}."
-                        " Only SELECT queries allowed."
-                    ),
-                    success=False,
-                )
+        forbidden = _FORBIDDEN_RE.search(_STRING_LITERAL_RE.sub("''", query))
+        if forbidden:
+            return ToolResult(
+                tool_name="knowledge_sql",
+                content=(
+                    f"Query contains forbidden keyword: {forbidden.group(1).upper()}."
+                    " Only SELECT queries allowed."
+                ),
+                success=False,
+            )
 
         try:
             rows = self._store._conn.execute(query).fetchmany(_MAX_ROWS)
-        except sqlite3.OperationalError as exc:
+        except sqlite3.Error as exc:
             return ToolResult(
                 tool_name="knowledge_sql",
                 content=f"SQL error: {exc}",

tests/evals/test_use_case_benchmarks.py

@@ -347,7 +347,7 @@ class TestCostCalculator:
             calls_per_month=1000,
             avg_input_tokens=500,
             avg_output_tokens=200,
-            provider_key="gpt-5.3",
+            provider_key="gpt-5.6-sol",
         )
         assert est.monthly_cost > 0
         assert est.annual_cost == est.monthly_cost * 12

tests/tools/test_knowledge_sql.py

@@ -64,6 +64,41 @@ def test_rejects_drop(store: KnowledgeStore) -> None:
     assert not result.success
 
 
+def test_allows_select_with_keyword_substring(store: KnowledgeStore) -> None:
+    """A read-only SELECT must not be rejected because a column/alias merely
+    contains a write keyword as a substring (e.g. 'created' -> CREATE)."""
+    from openjarvis.tools.knowledge_sql import KnowledgeSQLTool
+
+    tool = KnowledgeSQLTool(store=store)
+    result = tool.execute(
+        query="SELECT author AS created_author FROM knowledge_chunks"
+    )
+    assert result.success, result.content
+    assert "Alice" in result.content
+
+
+def test_allows_keyword_inside_string_literal(store: KnowledgeStore) -> None:
+    """A write keyword appearing only inside a string literal must not be
+    treated as a forbidden statement."""
+    from openjarvis.tools.knowledge_sql import KnowledgeSQLTool
+
+    tool = KnowledgeSQLTool(store=store)
+    result = tool.execute(
+        query="SELECT content FROM knowledge_chunks WHERE content LIKE '%delete%'"
+    )
+    assert result.success, result.content
+
+
+def test_rejects_multi_statement(store: KnowledgeStore) -> None:
+    """Multi-statement strings fail with a ToolResult, not an exception."""
+    from openjarvis.tools.knowledge_sql import KnowledgeSQLTool
+
+    tool = KnowledgeSQLTool(store=store)
+    result = tool.execute(query="SELECT 1; VACUUM")
+    assert not result.success
+    assert "error" in result.content.lower()
+
+
 def test_handles_bad_sql(store: KnowledgeStore) -> None:
     from openjarvis.tools.knowledge_sql import KnowledgeSQLTool