Prompt Cache

SHA-256 prompt deduplication for LLM and TTS calls — hash normalize prompts, check cache before calling APIs, store results for instant replay. Use when maki...

Do not assume this will work out of the box. Before installing or using: (1) confirm how the 'database' module is provided — the skill does not declare or install a DB adapter or connection details; (2) fix the schema/SQL mismatch (SKILL.md's CREATE TABLE lacks prompt_text but the code INSERTs prompt_text) or adjust the INSERT to match the schema; (3) ensure DB connection credentials/config are specified (and declared in requires.env) and stored securely; (4) consider removing the broad exception swallow in set_cached so cache failures are visible; (5) decide whether the truncated hash (first 32 hex chars) and inconsistent normalization (language not lowercased in hash) are acceptable for your collision/lookup needs. If the author provides a corrected release addressing these points (clear DB adapter, declared env vars, matching schema), the skill would be coherent; in its current form it is unreliable and potentially misleading.

Type: OpenClaw Skill Name: prompt-cache Version: 1.0.0 The skill implements a prompt caching mechanism using SHA-256 hashing and a platform-provided database. The `SKILL.md` explicitly declares `network.outbound: false` and the Python code adheres to this, making no external network calls. Database interactions use parameterized queries, preventing SQL injection. There are no signs of data exfiltration, malicious execution, persistence mechanisms, or prompt injection attempts against the agent. A minor functional bug exists in `scripts/prompt_cache.py` where `set_cached` attempts to insert into a `prompt_text` column not defined in the `SKILL.md` schema, which would cause caching to fail silently but without security implications.