Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DSmmartin/skills_talk_agent_camp_2026npx agentmods add skills/dsmmartin/skills_talk_agent_camp_2026/02_agent_assistedWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dsmmartin/skills_talk_agent_camp_2026/02_agent_assisted)<a href="https://agentmods.dev/skills/dsmmartin/skills_talk_agent_camp_2026/02_agent_assisted"><img src="https://agentmods.dev/badge/skills/dsmmartin/skills_talk_agent_camp_2026/02_agent_assisted/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dsmmartin/skills_talk_agent_camp_2026/02_agent_assisted"><img src="https://agentmods.dev/badge/skills/dsmmartin/skills_talk_agent_camp_2026/02_agent_assisted.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00051 | $0.00734 |
| Opus 5 | $0.00026 | $0.00367 |
| Sonnet 5 | $0.00010 | $0.00147 |
| Haiku 4.5 | $0.00005 | $0.00073 |
Grade A, and why
schema-sync-agent-assisted scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Schema Sync — Agent Assisted
Context
This system has four layers that break simultaneously when the database schema changes:
| Layer | File / System | What breaks |
|---|---|---|
| YAML contract | agentic_system/schema/github_events.yaml |
Contract no longer matches live DB |
| NL2SQL prompt | agentic_system/agents_core/nl2sql/prompts/system.md |
Agent generates SQL with old predicates → 0 rows, no error |
| RAG prompt | agentic_system/agents_core/rag/prompts/system.md |
Agent describes wrong field semantics to the user |
| ChromaDB chunks | schema_docs, qa_examples collections |
RAG retrieves stale context with wrong field names |
Repair procedure
Step 1 — Introspect live schema
Query ClickHouse to see what the database actually has:
SELECT name, type FROM system.columns WHERE table = 'github_events' ORDER BY position
Use connection settings from agentic_system/config.py (host, port, user, password, database).
Step 2 — Diff against YAML contract
Load agentic_system/schema/github_events.yaml and compare column names and types.
Identify: removed columns, added columns, type changes.
Step 3 — Patch YAML contract
Update agentic_system/schema/github_events.yaml:
- Add entries for new columns with correct type and a clear post-migration description.
- Update the type field for any column whose type changed.
- Update descriptions for migration-sensitive columns (especially merge-related fields).
Step 4 — Patch agent prompts
In both system.md prompt files:
- Replace old field name references with new names.
- Replace old SQL predicates (e.g.
field = 1) with new equivalents (e.g.field IS NOT NULL). - Update any type annotations in the schema table within the prompt.
- Update state labels (
pre-migration→post-migration).
Step 5 — Patch ChromaDB chunks
Connect to ChromaDB at http://localhost:8000 (settings from agentic_system/config.py).
For each collection (schema_docs, qa_examples):
- Get all items:
POST /api/v2/tenants/default_tenant/databases/default_database/collections/{id}/getwith{"include": ["documents", "metadatas"]} - Find items where
metadata.stale == True. - Apply the same text replacements to the document content.
- Re-embed using the deterministic hash function (64 dimensions, same algorithm as
db/vectordb/init/seed_vectors.py). - Upsert back:
POST .../upsertwith updated documents, embeddings, and metadata (stale: false,schema_state: post_migration_synced).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 74 lines · 51 tokens per session scan A a04144254e64
schema-sync-agent-assisted is a skill published in the GitHub repository DSmmartin/skills_talk_agent_camp_2026 (9 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 51 tokens to every session and 734 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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