Align copy with the post

README.md

@@ -6,13 +6,15 @@ colorTo: gray
 sdk: static
 pinned: false
 license: cc-by-sa-4.0
-short_description: "P&ID to a graph: VLM symbols, classic CV connections"
+short_description: "Your P&ID drawing, now data you can ask"
 ---
 
 # pid-parser showcase
 
-Precomputed results of [pid-parser](https://github.com/dzakybd/pid-parser) on one very dense P&ID sheet (190 symbols, 732 connected pairs), run two ways, the skill on Claude Sonnet 5.5 and the Deep Agents runner on gpt-6-luna: the drawing with the symbols the model found, the connections found by traditional computer vision, the graph, the tables, and the SQL, CSV, GraphML and Cypher exports. The page calls no model.
+Turn a P&ID drawing into data you can ask: SQL tables and a graph that people and AI agents can query. A vision model finds the symbols, and traditional computer vision (thresholding and connected-component labeling) finds the connections.
 
-Install the skill in your own agent with `npx skills add dzakybd/pid-parser`. How it works, step by step: [the write-up](https://dzaky.ai.id/en/blog/pid-parser-pid-to-graph).
+Precomputed results of [pid-parser](https://github.com/dzakybd/pid-parser) on one very dense P&ID sheet (190 symbols, 732 connected pairs), run two ways, the skill on Claude Sonnet 5.5 and the Deep Agents runner on gpt-6-luna. Each run shows the drawing with the symbols found, the graph, the tables, and the SQL, CSV, GraphML and Cypher exports. The page calls no model.
+
+Two versions: a skill for coding agents (`npx skills add dzakybd/pid-parser`) and a LangChain Deep Agents version for your own agent workflow. How it works, step by step: [the write-up](https://dzaky.ai.id/en/blog/pid-parser-pid-to-graph).
 
 Drawing: sheet 269 of the "Dataset PID" part of [PID2Graph](https://zenodo.org/records/14803338) ([paper](https://arxiv.org/abs/2411.13929)), CC BY-SA 4.0. The drawings and the outputs derived from them are shared under CC BY-SA 4.0. The pid-parser code is MIT licensed.

index.html

@@ -53,10 +53,10 @@ footer { margin-top: 28px; font-size: 13px; color: var(--muted); }
 </head>
 <body>
 <main>
-  <h1>pid-parser</h1>
-  <p class="muted">A P&amp;ID image in, tables and a graph out. A vision-language model finds the symbols tile by tile; the connections come from traditional computer vision (thresholding and connected-component labeling, no model); small scripts validate the graph and export it for SQL or a graph database. No GPU, no training.</p>
+  <h1>Your P&amp;ID drawing, now data you can ask</h1>
+  <p class="muted">SQL tables and a graph that people and AI agents can query. A vision-language model finds the symbols tile by tile; the connections come from traditional computer vision (thresholding and connected-component labeling, no model); small scripts validate the graph and export it. No GPU, no training.</p>
   <pre>npx skills add dzakybd/pid-parser</pre>
-  <p class="muted" style="margin-top:8px">Works in Claude Code, Codex and other skill-aware agents, or as a LangChain Deep Agent. Source: <a href="https://github.com/dzakybd/pid-parser">github.com/dzakybd/pid-parser</a>. How it works, step by step: <a href="https://dzaky.ai.id/en/blog/pid-parser-pid-to-graph">the write-up</a>. The sheet is one very dense P&amp;ID (190 symbols, 732 connected symbol pairs); the two tabs are two runs on it. These results were computed ahead of time; this page calls no model.</p>
+  <p class="muted" style="margin-top:8px">Two versions: a skill for coding agents such as Claude Code and Codex, and a LangChain Deep Agents version for your own agent workflow. Source: <a href="https://github.com/dzakybd/pid-parser">github.com/dzakybd/pid-parser</a>. How it works, step by step: <a href="https://dzaky.ai.id/en/blog/pid-parser-pid-to-graph">the write-up</a>. The sheet is one very dense P&amp;ID (190 symbols, 732 connected symbol pairs); the two tabs are two runs on it. These results were computed ahead of time; this page calls no model.</p>
 
   <div class="tabs" id="tabs" role="group" aria-label="Sheet"></div>
   <div class="stats" id="stats"></div>