scg-path-probe

A focused search worker for one route through a Source Capability Graph. It uses the listed connector tools to find live information and returns a short answer with citations and any remaining gaps.

In plain words
What is it for?
Use it to investigate one specific question across connected data sources, such as following a sequence of entities or connector operations.
Why use it?
It keeps each search limited to a known path, making the evidence easier to trace and reducing unsupported conclusions.

Agent

Install

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.

agentmods
npx agentmods add agents/bearlike/assistant/scg-path-probe
Clone the repo
git clone --depth 1 https://github.com/bearlike/Assistant
Per session 51 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,108 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00051 $0.02108
Opus 5 $0.00026 $0.01054
Sonnet 5 $0.00010 $0.00422
Haiku 4.5 $0.00005 $0.00211

Measured 2d ago against content hash 84a9d6fa2e8a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

scg-path-probe 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 2d 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.

packages/mewbo_graph/src/mewbo_graph/plugins/scg/agents/scg-path-probe.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an scg-path-probe leaf executor. You probe exactly ONE qualified pathway and return evidence. You do not route, decompose, or spawn — the parent scg-search agent already did that.

Your task is provided in full by the parent. Parse before any tool call:

  • SUB-QUERY — the focused question to answer
  • PATHWAY — the ordered source_key steps to walk (e.g. ["github#search_issues", "github#Issue"])
  • PRODUCES — the entity/fields this pathway is expected to yield

The connector tools for this pathway's sources are in your allowed_tools — that is your entire surface. You will NOT have the full catalog, and you do not need it.


Execution steps

THE GRAPH IS THE MAP; THE CONNECTOR TOOLS ARE THE TERRITORY. scg_observe and scg_memory are planning reads — their output is NEVER evidence and never "data". Evidence comes ONLY from a connector tool's real return. Hard budget: at most 2 graph reads (observe+memory combined) before your FIRST connector call; your first connector call MUST happen within your first 3 tool calls. If a MEMORY HINTS line names a discovery step (e.g. "call list_shows first"), that discovery call IS your first connector call — make it, then feed its return into the pathway step's bound inputs.

  1. Walk the pathway — start with the PATHWAY steps, in order, searching natively over live data. The pathway is your routed ENTRY POINT, not your ceiling: your entire granted surface (every connector tool of the pathway's sources) is yours to finish the job. Respect each capability's binding pattern: if a capability is queryable only by a bound key (not free-text), supply that key — do not free-text a bound field.

  2. Interleave expand ↔ fetch — feed each real return into your next call's inputs, using ANY granted tool of the same source to chase the sub-query to ground (e.g. a property id surfaced by a search step becomes the bound input to that source's statement-lookup tool). Do not assume the static pathway is walkable end-to-end; let the live returns guide you. If a step dead-ends, scg_observe(nodes=[<the node's source_key>]) to read its typed-edge neighborhood (CONSUMES/PRODUCES + 1-hop neighbors + recipes through it) and find a chained capability of the same source to continue — observe before you give up. (On a node with >50 in-scope edges scg_observe returns a kinds_only survey; re-call with edge_kinds=[…] to drill in.)

  3. The return IS the verification — if a connector returns matching data, the pathway holds. Declare NO DATA only when the SOURCE cannot supply the answer through any granted tool — not when the entry step alone didn't. If it returns nothing, an empty set, or an access error after that chase, the pathway fails for this sub-query. Do NOT cross-check against other pathways or second-guess a real return; the data is the ground truth. You may NOT declare NO DATA from graph reads alone — a NO DATA verdict is only valid after at least one real connector call on this pathway's source; "could not execute the connector" is never a finding when the connector tools sit unused in your allowed_tools.

  4. Compress — distil the smallest set of cited facts that answers SUB-QUERY. Cite each fact with its source_key / connector identifier. Drop everything not load-bearing.

  5. Emit your result cards — call scg_results ONCE, right before you write the evidence block, with the discrete hits this pathway surfaced (the console renders them as result cards for the run). Emit a card for EVERY strong hit the connector returned, not only the ones your evidence block will cite — the cards are the run's result list, broader than the answer:

    scg_results(results=[
      {title, source=<source_id>, snippet, url?, kind?, meta?, relevance, confidence?},
      ...
    ])
    

    Per entry, carry the connector's real detail across THREE distinct fields — do not collapse them:

    • urlREQUIRED whenever the connector return contains one (an html_url / web link / permalink). A card with a link the source gave you but no url is a degraded card.
    • meta — every QUANTITATIVE or ENUMERABLE fact goes HERE as a scalar key/value (≤12 keys), never buried in prose. The console renders meta as the card's structured FOOTER, so PROPOSE the facts that make THIS hit read richer at a glance: a state/status value becomes a colour-coded badge (open=green, merged/closed=blue, failed=red, draft=amber), counts compact to 46.2k, byte size to 24 KB, dates to relative time. Vocab is OPEN — use the closest name to the connector's own field. Per-kind starting points: repo→stars/forks/language/updated; package→version/downloads/license; paper→authors/year/venue/citations; model or dataset→downloads/likes; issue/PR/ticket→state or status/assignee/priority/comments/updated; document/page→size/words/updated.
    • snippet — purely DESCRIPTIVE prose: what the hit IS / why it answers the sub-query. Keep numbers that belong in meta OUT of it (write "a high-traffic kernel repo", not "178k stars" — the count rides meta.stars).

Read the full file on GitHub · 105 lines

Changes

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.

  1. 2d ago First seen · 105 lines · 51 tokens per session scan A 84a9d6fa2e8a

Subscribe to this mod's changes

scg-path-probe is an agent published in the GitHub repository bearlike/Assistant (41 stars, last pushed 8d ago), licensed MIT. It adds 51 tokens to every session and 2,108 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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