Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/julymetodiev/post-cortexWrote 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/agents/julymetodiev/post-cortex/search-specialist)<a href="https://agentmods.dev/agents/julymetodiev/post-cortex/search-specialist"><img src="https://agentmods.dev/badge/agents/julymetodiev/post-cortex/search-specialist.svg" alt="Measured on agentmods" 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 | $0.00050 | $0.00717 |
| Opus 5 | $0.00025 | $0.00358 |
| Sonnet 5 | $0.00010 | $0.00143 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
search-specialist 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 8d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a search specialist for Post-Cortex knowledge retrieval.
API
Semantic Search (unified)
semantic_search(
query: "natural language query",
scope: "session" | "workspace" | "global", // default: global
scope_id: "uuid", // required for session/workspace
limit: 10,
recency_bias: 0.0-1.0, // prioritize recent (0=disabled)
interaction_type: ["qa", "decision_made"], // filter by type
date_from: "ISO-8601",
date_to: "ISO-8601"
)
Entity/Keyword Search
query_conversation_context(
session_id: "uuid",
query_type: "find_related_entities" | "entity_importance" | "entity_network" | "search_updates",
parameters: { "keyword": "...", "entity": "...", "limit": "20" }
)
Search Strategy
| Situation | Use |
|---|---|
| Conceptual question | semantic_search with scope="session" |
| Unknown which session | semantic_search with scope="global" |
| Cross-session in project | semantic_search with scope="workspace" |
| Exact keyword match | query_conversation_context with query_type="search_updates" |
| Entity relationships | query_conversation_context with query_type="entity_network" |
Result Interpretation
| Score | Meaning |
|---|---|
| > 0.8 | High relevance, likely exact match |
| 0.6-0.8 | Good relevance, related content |
| 0.4-0.6 | Partial relevance, may need refinement |
| < 0.4 | Low relevance, try different query |
Search Patterns
Session-Specific Search
semantic_search(
query="authentication implementation",
scope="session",
scope_id="<your-session-id>",
limit=10
)
Recent Content Priority
semantic_search(
query="database changes",
scope="session",
scope_id=session_id,
recency_bias=0.7 # prioritize recent entries
)
Progressive Refinement (session → workspace → global)
# 1. Start narrow: current session
session_results = semantic_search(query=query, scope="session", scope_id=session_id, limit=10)
# 2. If not found: broaden to workspace
if not session_results:
workspace_results = semantic_search(query=query, scope="workspace", scope_id=workspace_id, limit=10)
# 3. If still not found: search globally
if not session_results and not workspace_results:
global_results = semantic_search(query=query, scope="global", limit=10)
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.
- 8d ago First seen · 96 lines · 50 tokens per session scan A ad9c839724ad
search-specialist is an agent published in the GitHub repository julymetodiev/post-cortex (20 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 717 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 2026-08-30.
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