SKILLEMALL.ai

AB session-context-injector

Reorient a Telegram chat after a session reset. Reads a project's STATUS.md (resume point, blockers, next action) and sends a project-specific context injection message via the Telegram bot API. Use when: clearing session transcripts, creating new project rooms, or onboarding collaborators into a scoped chat. Supports 3 message variants: group refresh, direct DM summary, and new-room welcome.

ClawHub Agent Skills author: Nissan Dookeran v1.0.0 MIT-0 3 files body ≈ 1 946 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice

IntegrationTelegramInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
84
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 1

    ✓ No critical or high findings

    Medium and low: 1

    ✓ Guard found no suspicious behaviour. 1 matches are attack strings quoted in this security skill's own documentation.

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 65/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 8 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1946 tokens
    • 100Progress reporting. Reports progress
    • low 12 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (3 tags): a typed call is more reliable

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 395: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (8 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This instruction-only skill is purpose-aligned: it sends disclosed Telegram context-refresh messages from project status files, but users should verify recipients and avoid sending sensitive status details to the wrong chat.
    LLM: benign (high) · VirusTotal: · 29 May 2026